# templates

name: Binance SM 4hour Indicators Tool
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-06-06T18:20:34.879Z
updated_at: 2025-06-06T18:20:34.879Z
url: https://n8n.io/workflows/4745
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  A medium-term trend analyzer for the Binance Spot Market that leverages core technical indicators across 4-hour candle data to provide human-readable swing-trade signals via AI.

  🎥 Watch Tutorial:

  🎯 What It Does

  Accepts a Binance trading pair (e.g., AVAXUSDT)
  Sends the symbol to an internal webhook for technical indicator calculation
  Computes 4h RSI, MACD, Bollinger Bands, SMA, EMA, ADX
  Returns structured, GPT-analyzed signals ready for Telegram delivery

  🧠 AI Agent Details

  Model:** GPT-4.1-mini (OpenAI Chat)
  Agent Role:** Translates raw indicator values into sentiment-labeled signals
  Memory:** Tracks session + symbol context for cleaner multi-turn logic

  🔗 Required Backend Workflow

  To calculate indicators, this tool depends on:

  POST https://treasurium.app.n8n.cloud/webhook/4h-indicators
  {
    "symbol": "AVAXUSDT"
  }

  Returns a JSON object with the latest 40×4h candle-based calculations.

  📥 Input Format

  {
    "message": "AVAXUSDT",
    "sessionId": "telegram_chat_id"
  }

  📊 Sample Output

  🕓 4h Technical Signals – AVAXUSDT

  • RSI: 64 → Slightly Bullish  
  • MACD: Bullish Cross above baseline  
  • BB: Upper band touch – volatility expanding  
  • EMA &gt; SMA → Confirmed Upside Momentum  
  • ADX: 31 → Strengthening Trend

  📚 Use Case Scenarios

  | Use Case                      | Result                                               |
  | ----------------------------- | ---------------------------------------------------- |
  | Swing trend confirmation      | Uses 4h indicators to validate or reject setups      |
  | Breakout signal confluence    | Helps assess if momentum is real or noise            |
  | Inputs to Quant AI or Analyst | Supports higher-frame trade recommendation synthesis |

  🛠️ Setup Instructions

  Import the JSON template into your n8n workspace.
  Set your OpenAI API credentials for the GPT node.
  Ensure the /webhook/4h-indicators backend tool is live and accessible.
  Connect this to your Binance Financial Analyst Tool or master Quant AI orchestrator.

  🤖 Parent Workflows That Use This Tool

  Binance SM Financial Analyst Tool
  Binance Spot Market Quant AI Agent

  📎 Sticky Notes & Annotations

  This workflow includes internal sticky notes describing:

  Node roles (GPT, webhook, memory)
  System behavior (reasoning agent logic)
  Telegram formatting guidance

  🔐 Licensing & Attribution

  © 2025 Treasurium Capital Limited Company
  All architecture, prompt logic, and signal formatting are proprietary. Redistribution or rebranding is prohibited.

  🔗 Connect with the creator: Don Jayamaha – LinkedIn

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.executeWorkflowTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5724 characters]

metadata_json:
  {"categories":["AI/ML","Trading"],"complexity":"medium","use_cases":["analyze market trends","generate trading signals","calculate technical indicators"],"estimated_setup_minutes":15,"required_services":["Binance","GPT-4"],"key_features":["computes 4-hour RSI, MACD, Bollinger Bands, SMA, EMA, ADX","generates AI-analyzed swing-trade signals","delivers human-readable Telegram messages"],"target_audience":["traders","investors","financial analysts"]}


name: Binance SM 1day Indicators Tool
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-06-06T18:23:40.026Z
updated_at: 2025-06-06T18:23:40.026Z
url: https://n8n.io/workflows/4746
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This advanced agent analyzes long-term price action in the Binance Spot Market using 1-day candles. It calculates key macro indicators like RSI, MACD, BBANDS, EMA, SMA, and ADX to identify high-confidence trend setups and market momentum. Used by the Quant AI system for directional bias and macro-level signal validation.

  🎥 Watch Tutorial:

  🎯 Purpose

  Detect major trend reversals, consolidation zones, and macro bias
  Support long-term swing trading decisions
  Provide reliable 1-day signals for downstream agents

  🧠 Core Features

  | Feature                     | Description                                                  |
  | --------------------------- | ------------------------------------------------------------ |
  | 🔁 Trigger                  | Called by parent workflows via Execute Workflow            |
  | 📥 Input Format             | { "message": "MATICUSDT", "sessionId": "telegram_id" }     |
  | 📡 Webhook Call             | Sends request to internal 1d indicators webhook              |
  | 🧮 Technical Indicators     | RSI, MACD, BBANDS, EMA, SMA, ADX (based on 40 daily candles) |
  | 🧠 GPT (gpt-4.1-mini) Agent | Interprets numerical data into human-readable trend signals  |
  | 💬 Output                   | Summary suitable for Telegram or further agent consumption   |

  🔗 External Tools Called

  https://treasurium.app.n8n.cloud/webhook/1d-indicators

  Sends:

  {
    "symbol": "SOLUSDT"
  }

  📊 Indicator Calculations

  | Indicator      | Purpose                         |
  | -------------- | ------------------------------- |
  | RSI (14)       | Overbought / Oversold Signals   |
  | MACD (12,26,9) | Trend Reversals / Momentum      |
  | BBANDS (20, 2) | Volatility Expansion            |
  | EMA (20)       | Short-Term Trend Confirmation   |
  | SMA (20)       | Macro-Level Support/Resistance  |
  | ADX (14)       | Trend Strength + Directional DI |

  📦 Setup

  Import the JSON into n8n.
  Add your OpenAI API credentials.
  Ensure webhook /1d-indicators is connected and working.
  Use this agent as a sub-workflow in:

     Binance SM Financial Analyst Tool
     Binance Spot Market Quant AI Agent

  📤 Output Example

  📅 1D Overview – MATICUSDT

  • RSI: 71 → Overbought  
  • MACD: Bearish Cross forming  
  • BBANDS: Widening Volatility  
  • EMA &lt; SMA → Downtrend Momentum  
  • ADX: 33 → High Trend Strength

  📌 Notes

  Not user-facing — outputs are structured JSON or Telegram-style summaries.
  Pairs well with shorter timeframe tools (15m–4h) for confidence stacking.

  🧾 Licensing & Attribution

  © 2025 Treasurium Capital Limited Company
  Architecture, prompts, and trade report structure are IP-protected.
  No unauthorized rebranding permitted.

  🔗 Need help? Reach out on LinkedIn – Don Jayamaha

nodes_used:
[cell repeats an earlier one in this file: 361 characters]

workflow_json_compressed:
  [encoded data, 5628 characters]

metadata_json:
  {"categories":["Trading","Investing","Data Analysis"],"complexity":"medium","use_cases":["calculate technical indicators","identify trend reversals","analyze market momentum","generate swing trading signals","validate directional bias"],"estimated_setup_minutes":15,"required_services":["Binance API","Hpsilon AI"],"key_features":["1-day candle analysis","multi-indicator calculations","macro bias detection","long-term signal generation"],"target_audience":["quantitative traders","swing traders","risk managers"]}


name: Binance SM Indicators Webhook Tool
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-06-06T18:28:23.790Z
updated_at: 2025-06-06T18:28:23.790Z
url: https://n8n.io/workflows/4747
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow acts as a central API gateway for all technical indicator agents in the Binance Spot Market Quant AI system. It listens for incoming webhook requests and dynamically routes them to the correct timeframe-based indicator tool (15m, 1h, 4h, 1d). Designed to power multi-timeframe analysis at scale.

  🎥 Watch Tutorial:

  🎯 What It Does

  Accepts requests via webhook with a token symbol and timeframe
  Forwards requests to the correct internal technical indicator tool
  Returns a clean JSON payload with RSI, MACD, BBANDS, EMA, SMA, and ADX
  Can be used directly or as a microservice by other agents

  🛠️ Input Format

  Webhook endpoint:

  POST /webhook/indicators

  Body format:

  {
    "symbol": "DOGEUSDT",
    "timeframe": "15m"
  }

  🔄 Routing Logic

  | Timeframe | Routed To                        |
  | --------- | -------------------------------- |
  | 15m       | Binance SM 15min Indicators Tool |
  | 1h        | Binance SM 1hour Indicators Tool |
  | 4h        | Binance SM 4hour Indicators Tool |
  | 1d        | Binance SM 1day Indicators Tool  |

  🔎 Use Cases

  | Use Case                                           | Description                                            |
  | -------------------------------------------------- | ------------------------------------------------------ |
  | 🔗 Used by Binance Financial Analyst Tool          | Automatically triggers all indicator tools in parallel |
  | 🤖 Integrated in Binance Quant AI System           | Supports reasoning, signal generation, and summaries   |
  | ⚙️ Can be called independently for raw data access | Useful for dashboards or advanced analytics            |

  📤 Output Example

  {
    "symbol": "DOGEUSDT",
    "timeframe": "15m",
    "rsi": 56.7,
    "macd": "Bearish Crossover",
    "bbands": "Stable",
    "ema": "Price above EMA",
    "adx": 19.4
  }

  ✅ Prerequisites

  Make sure all the following workflows are installed and operational:

    Binance SM 15min Indicators Tool
    Binance SM 1hour Indicators Tool
    Binance SM 4hour Indicators Tool
    Binance SM 1day Indicators Tool
  OpenAI credentials (for any agent using LLM formatting)

  🧾 Licensing & Attribution

  © 2025 Treasurium Capital Limited Company
  All architectural routing logic and endpoint structuring is IP-protected.
  No unauthorized rebranding or resale permitted.

  🔗 Need help? Connect on LinkedIn – Don Jayamaha

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.webhook","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.webhook","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["DevOps","Data Processing"],"complexity":"medium","use_cases":["route API requests","timeframe based indicator calculation","central gateway management"],"estimated_setup_minutes":15,"required_services":["Binance API","Custom Webhook Endpoints"],"key_features":["Webhook request routing","Dynamic service dispatching","Multi-timeframe support","JSON response formatting"],"target_audience":["quantitative analysts","algorithmic traders","backend developers"]}


name: AI Email Auto-Responder System- AI RAG Agent for Email Inbox
author_name: LukaszB
author_username: lukaszb
categories: []
created_at: 2025-06-06T19:16:47.224Z
updated_at: 2025-06-06T19:16:47.224Z
url: https://n8n.io/workflows/4748
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  AI Email Auto-Responder – Smart Client Reply Automation with RAG

  This workflow is built for individuals, teams, and businesses that receive regular inquiries via email and want to automate responses in a way that’s intelligent, brand-aligned, and always up to date. Its core purpose is to generate high-quality, professional email replies using internal company data, brand voice, and semantic search — fully automated through Gmail, Pinecone, and OpenAI.

  The system is divided into three steps. First, it allows you to index your internal knowledge base (Docs, Sheets, PDFs) with embeddings. Second, it injects a consistent brand brief into every interaction to ensure tone and positioning. Finally, the main flow listens for incoming emails, understands the user query, retrieves all needed data, and writes a full HTML reply — sending it directly to the original thread via Gmail.

  This solution is ideal for support teams, solopreneurs, B2B service providers, or anyone looking to scale high-quality client communication without scaling manual work. It can be extended to handle multilingual queries, intent routing, or CRM logging.

  How it works

  When a new email arrives in Gmail, the workflow checks whether it's a valid client inquiry. If so, it:
  Extracts the subject and message content
  Sends the message through OpenAI to understand the question
  Queries a Pinecone vector database (populated via a separate embedding workflow) to find relevant internal knowledge
  Loads a brand brief from a Google Doc or Notion block
  Combines retrieved data and brand context to generate a clear, structured HTML reply using OpenAI
  Sends the reply via Gmail and logs the message

  This process ensures every reply is relevant, accurate, and consistent with your brand — and takes under 10 seconds.

  Set up steps

  Getting started takes about 30–60 minutes.

  Create three workflows: one for embedding documents (Step 1), one sub-workflow for the brand brief (Step 2), and one main responder flow (Step 3)
  Connect the following APIs: Gmail (OAuth2), OpenAI, Pinecone, Google Drive, and optionally Notion
  Replace all placeholders: folder ID in Google Drive, Pinecone index and namespace, your brand brief URL or doc ID, and Gmail credentials
  Test your embedding workflow by uploading a document and verifying its presence in Pinecone
  Trigger the responder by sending an email and reviewing the AI’s reply

  Detailed setup instructions are stored in sticky notes within each workflow to guide you through configuration.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.toolVectorStore","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.gmailTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.notion","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDocs","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Communication","Knowledge Management"],"complexity":"medium","use_cases":["automate email responses","retrieve company data for context","generate brand-aligned replies","manage inbox workload","search internal knowledge base"],"estimated_setup_minutes":60,"required_services":["Gmail API","Pinecone","OpenAI","Google Drive","Notion"],"key_features":["RAG (Retrieval-Augmented Generation)","semantic search","vector database integration","dynamic context retrieval","automated inbox management"],"target_audience":["customer support teams","business owners","knowledge managers"]}


name: Payment Processing and Order Tracking with YooKassa and Google Sheets
author_name: Sergey Skorobogatov
author_username: cepreusa
categories: []
created_at: 2025-06-06T22:41:32.579Z
updated_at: 2025-06-06T22:41:32.579Z
url: https://n8n.io/workflows/4749
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Accept YooKassa payments and log transactions in Google Sheets

  🧾 Summary

  This workflow allows you to accept online payments via YooKassa and log both orders and transactions in Google Sheets — all without writing a single line of code. It supports full payment flow: product selection, payment initiation, webhook processing, refund updates, and payment status checks.

  👥 Who is this for?

  This template is ideal for:

  Online stores with simple checkout flows
  Sellers of digital products or info-courses
  Entrepreneurs using Telegram bots or web forms
  Anyone needing quick payment integration with Google Sheets tracking

  🎯 What problem does this workflow solve?

  Setting up online payments usually requires backend infrastructure. This no-code solution automates the entire payment flow:

  Handles product listing and price retrieval
  Initiates payments with email and return URL
  Listens for payment.succeeded and refund.succeeded events
  Records every action into structured Google Sheets

  ⚙️ What this workflow does

  1. GET /products

  Returns a sorted list of products from a Google Sheet (products).

  2. POST /payment

  Validates required fields (product_id, email, return_url)
  Checks email format
  Fetches product data from products
  Generates a unique idempotence key
  Sends a request to YooKassa API
  Saves the order into the orders sheet
  Returns a payment confirmation link

  3. POST /yoomoney

  Webhook to process payment/refund events:

  On payment.succeeded, adds entry to transactions
  On refund.succeeded, updates transaction status

  4. GET /status/\:id

  Returns real-time payment status from YooKassa

  🚀 Setup

  Connect credentials:

     Google Sheets (OAuth2)
     YooKassa (Basic Auth using shopId and secretKey)

  Update the following Google Sheets:

     products: should contain product_id, title, price
     orders: for saving confirmed purchases
     transactions: for logging all successful or refunded payments

  Test endpoints using any HTTP client:

  Example payload for /payment:

  {
    "product_id": "abc123",
    "email": "user@example.com",
    "return_url": "https://your.site/success"
  }

  🔧 How to customize this workflow

  Add delivery logic (e.g., email with product link after successful payment)
  Replace Google Sheets with a database (e.g., PostgreSQL)
  Connect Telegram or other messengers for post-payment notifications
  Add promo codes, discounts, or subscriptions logic

  💼 Use cases

  Simple online checkouts
  Telegram bots selling access
  Educational product sales
  MVP e-commerce flows
  Donation or membership payments

  📎 Notes

  ✅ Includes Sticky Notes for sections
  ✅ Includes error handling and validation
  ✅ No custom code needed except UUID generation

nodes_used:
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workflow_json_compressed:
  [encoded data, 8700 characters]

metadata_json:
  {"categories":["E-commerce","Finance","Data Processing"],"complexity":"medium","use_cases":["Process online payments","Track orders in spreadsheets","Log transactions","Handle refunds","Check payment status"],"estimated_setup_minutes":30,"required_services":["YooKassa","Google Sheets"],"key_features":["Webhook processing","Payment flow automation","Transaction logging","Refund handling","Payment status verification"],"target_audience":["E-commerce sellers","Online store owners","Financial service providers"]}


name: fetch the public IP addresses of your n8n instance
author_name: Ger Longstacks
author_username: dims3body
categories: []
created_at: 2025-06-06T23:26:40.460Z
updated_at: 2025-06-06T23:26:40.460Z
url: https://n8n.io/workflows/4750
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Why
  If you need to use n8n to connect to service providers of yours,  some of which happen to  rely on firewall white-listing as part of their access control, you'll need to determine or verify the public IP addresses of your n8n instance(s).

  How does it work
  The webhook, upon invocation, will use Http Request node to request public IP address information from ++api.ipify.org++ in json format, for 10 times, then aggregate results to an array.
    The reason to repeat, is to get all the potential public IP addresses of your n8n instance.
    Often than not, enterprises or network providers deploy at least a pair of gateway devices at the border for redundancy.
  built-in array functions in a javascript expression are used to pluck all the values under 'ip' key, and to dedup to an array as response body.

  How to set it up
  import the workflow
  set up your own header-auth credential
  update the workflow to use the new credential
  test or activate workflow as usual.

  example invocation
  $ curl -H "api-key: super-long-api-token" http://localhost:5678/webhook-test/4879bc79-d6f8-48df-bfe4-613366c7f399
  ["88.88.88.66", "88.88.88.88"]

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.aggregate","n8n-nodes-base.set"]

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metadata_json:
  {"categories":["DevOps"],"complexity":"simple","use_cases":["retrieve public IP","verify external access"],"estimated_setup_minutes":5,"required_services":["ipify.org"],"key_features":["multi-call aggregation"],"target_audience":["devops engineers","network admins"]}


name: Automated Video Translation & Distribution with DubLab to Multiple Platforms
author_name: Behram
author_username: behram
categories: []
created_at: 2025-06-07T02:21:31.652Z
updated_at: 2025-06-07T02:21:31.652Z
url: https://n8n.io/workflows/4751
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Automated n8n workflow: Receives videos via form, dubs/translates them to the selected languages, and—upon completion—uploads them to multiple social media channels and cloud drives, including Box, Dropbox, and YouTube, Telegram, Postiz (Facebook, Instagram, Tiktok, Reddit etc.)

  Workflows
  Via n8n form select files to dub for desired languages.
   Listen webhook and whenever dubbing finishes upload to desired platforms

  Used Stacks
  DubLab App (ApiKey, Webhook Setup Required)
  Optional (Upload)
   Telegram (Token Required)
   Box (Oauth2 Required)
   Dropbox (Oauth2 Required)
   Youtube (Oauth2 Required)
   Postiz (ApiKey Required)

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.webhook","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.box","n8n-nodes-base.dropbox","n8n-nodes-base.youTube","n8n-nodes-base.httpRequest","n8n-nodes-base.formTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Communication","Media Management","Automation"],"complexity":"medium","use_cases":["Automate video dubbing and distribution across social platforms","Centralize video upload and storage in cloud drives and social networks","Process user-submitted video files and translate them to multiple languages"],"estimated_setup_minutes":30,"required_services":["DubLab","Box","Dropbox","YouTube","Telegram","Postiz"],"key_features":["Multi-language video dubbing integration","Automated social media posting","Cross-platform cloud storage sync","Form-based input handling"],"target_audience":["social media managers","content creators","marketing teams"]}


name: ♻️ AI multi-stop planner for circular logistics with GPT-4o & Open Route API
author_name: Samir Saci
author_username: samirsaci
categories: []
created_at: 2025-06-07T08:20:33.015Z
updated_at: 2025-06-07T08:20:33.015Z
url: https://n8n.io/workflows/4753
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Tags*: AI Agent, Supply Chain, Logistics, Circular Economy, Route Planning, Transportation, GPS API

  Context

  Hi! I’m Samir — a Supply Chain Engineer and Data Scientist based in Paris, and founder of LogiGreen Consulting.

  I help logistics teams reduce operational workload and errors by combining AI automation, route optimisation APIs, and workflow automation.

  This workflow is part of a circular economy project, where stores return reusable packaging (bins, crates, containers) to a central warehouse.

  &gt; Let's create circular economies with AI-powered automation using n8n!

  📬 For business inquiries, you can find me on LinkedIn

  Who is this template for?

  This workflow is designed for logistics teams participating in circular economy loops.

  Let us imagine your transportation company receives this pickup request:



  The two AI Agent nodes connected to Openroute Service API will process the information and reply with the detailed route plan.



  The results include driving time and the optimal sequence of stops generated by the multi-stop optimization endpoint of the API.

  How does it work?

  This workflow automates the end-to-end processing of multi-stop pickup requests for reusable packaging:

  📨 Gmail Trigger listens for collection request emails  
  🧠 AI Agent parses the email into structured data (store ID, address, date)  
  📍 Each stop is geocoded into GPS coordinates  
  🗺️ OpenRouteService optimizes the stop sequence using truck-specific routing  
  📄 A second AI Agent formats a confirmation email in HTML with the ordered pickup plan  
  📧 The reply is sent back with all details including duration and route

  Steps:

  💌 Trigger on a new Gmail message  
  🧠 Extract data using AI Agent (e.g., stores, addresses, times)  
  📑 Store raw and processed data in Google Sheets  
  📍 Enrich with GPS coordinates  
  🚚 Optimize route using OpenRouteService (truck profile)  
  📄 Format the confirmation using an AI Agent  
  📬 Send reply to requester with route and timing

  What do I need to get started?

  You’ll need:

  A Gmail account to receive collection requests  
  A Google Sheet to store and review data  
  A free OpenRouteService API key  
  Access to OpenAI for using AI Agent nodes  
  Sample pickup request emails to test

  Next Steps

  🗒️ Use the sticky notes inside the n8n canvas to:

  Plug in your Gmail and OpenRouteService credentials  
  Try with a sample store collection email  
  Validate the confirmation format and route accuracy

  📺 Learn More with n8n Tutorials 

  Get hands-on experience with automation through my comprehensive n8n tutorial playlist, featuring 18+ complete, step-by-step videos and ready-to-use templates.




  This template was built using n8n v1.93.0  
  Submitted: June 7, 2025

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metadata_json:
  {"categories":["Logistics","Supply Chain","AI/ML"],"complexity":"medium","use_cases":["Automate multi-stop route planning","Optimize packaging return trips","Coordinate circular logistics assets"],"estimated_setup_minutes":15,"required_services":["Open Route Service API","OpenAI GPT-4o","Google Sheets","Airtable"],"key_features":["Handles multi-leg routing","Sorts optimized sequences","Processes geospatial data","Generates detailed invoices","Extracts structured data"],"target_audience":["Supply chain engineers","Logistics managers","Route planners"]}


name: Post AI Videos to YouTube with Fal AI Veo3, Google Sheets, and YouTube API
author_name: Ari Nakos
author_username: just-aristides
categories: []
created_at: 2025-06-07T08:20:59.571Z
updated_at: 2025-06-07T08:20:59.571Z
url: https://n8n.io/workflows/4754
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Auto-Post Veo3 Videos on YouTube

  An automated workflow for creating Veo3 videos and posting them to YouTube. 

  YT Tutorial: https://youtu.be/DXM1VA-vDX4

  Workflow Overview

  The workflow is divided into three main phases:

  Create Veo3 Video
  Wait for Video Processing
  Post on YouTube

  1. Create Veo3 Video

  This phase handles the initial video creation based on user input.

  Type Prompt:** A form trigger allows the user to input details for the video, including:
      Prompt: A simple scenario for the video.
      Video Style: (e.g., Dialogue, Monologue, Advertisement, Documentary)
      Aspect Ratio: (e.g., 16:9, 9:16, 1:1)
      Video Category: A YouTube category for the video.
  Get Specific Prompt:** Based on the selected "Video Style," the workflow fetches specific prompt data from a Google Sheet.
  Videography (AI Refinement):** An AI agent (using OpenRouter's Google Gemini 2.5 Flash model) refines the user's prompt into a detailed "script-to-screen" format suitable for video generation.
  Make FAL.AI Request:** The refined prompt is sent to the Fal.ai Veo 3 model via an HTTP request to generate the video. The video duration is fixed at 8 seconds.
  Store Data:** Details of the video request, including the date requested, the refined prompt, and the request URL, are stored in a Google Sheet.

  2. Wait for Video Processing

  Wait 5 mins:** The workflow pauses for 5 minutes. This waiting period is necessary as it typically takes 3-5 minutes for the video to be ready after the generation request.

  3. Post on YouTube

  This phase focuses on generating YouTube SEO details and uploading the video.

  YT Video SEO (AI Generation):** An AI agent (using OpenRouter's OpenAI GPT-4.1 Mini model) acts as a YouTube SEO specialist and viral content strategist. It generates the following details for the YouTube video:
      Video Title: A compelling title (less than 6 words).
      Video Description: A detailed description.
      Video Tags: Relevant tags to maximize discoverability.
      YouTube Category: The appropriate YouTube category code based on the user's input.
      The AI agent is configured to follow guidelines for virality and YouTube's tag limits.
  Structured Output:** Parses the structured JSON output from the AI agent.
  Get Keywords:** Extracts and formats the video tags into a comma-separated list suitable for YouTube.
  Fetch Video Credentials:** Fetches the video URL and other credentials from Fal.ai.
  Download Video:** Downloads the generated video file.
  Post on YouTube:** The video is uploaded to YouTube using the generated title, description, tags, and category.

  Setup

  To run this workflow, you need to set up credentials in n8n for:

  OpenRouter:** Generate API key from your OpenRouter account.
  Google Sheets:** Uses OAuth 2.0. Connect by authenticating your Google account.
  YouTube Data API:** Configure credentials to allow posting videos to YouTube.

  If you do not have an n8n account, follow the tutorial at https://youtu.be/E2yQelHPUdU?feature=shared to get started.

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metadata_json:
  {"categories":["AI/ML","Content Creation","Marketing"],"complexity":"medium","use_cases":["automate video generation","publish YouTube content","integrate AI video tools"],"estimated_setup_minutes":15,"required_services":["Fal AI","YouTube API","Google Sheets"],"key_features":["form trigger","video creation automation","YouTube auto-posting"],"target_audience":["content creators","video marketers"]}


name: Chat with PDF / MD / Text Files using GraphRAG (no vector store needed)
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-06-07T09:42:46.538Z
updated_at: 2025-06-07T09:42:46.538Z
url: https://n8n.io/workflows/4755
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  Set up a chat with your documents without the complex vector store setup.

  This templates helps you 
  ingest** your PDF / text / MD documents into a knowledge graph
  use the graph as the knowledge base for your AI chatbots (and other workflows)
  visualize the main topics* and *gaps** in your documents (good for observability and research)


  The knowledge base is provided using the InfraNodus GraphRAG with the knowledge graphs  offering high-quality responses without the need to set up complex RAG vector store workflows.

  The advantages of using GraphRAG instead of the standard vector stores for knowledge are:

  Easy and quick to set up and update** — no complex data import workflows needed
  A knowledge graph offers a holistic and interactive view of your knowledge base (accessible via our API or a web interface — also shareable)
  Better retrieval of relations** between the document chunks = higher quality responses

  How it works
  This template uses the InfraNodus knowledge graph as a knowledge base for your n8n AI agent node.

  The knowledge graph contains the documents you can upload using this template from your Google Drive.

  When the user asks a question via the chat interface, the agent forwards this question to the InfraNodus knowledge graph, retrieves a response, a summary, and a list of matching statements (based advanced Graph RAG), then delivers the final response back the user.

  Here's a description step by step:

  Step 1: Upload your documents
  Put the PDF / text / MD files you want to chat with into a folder on your Google drive
  Authorize access to that folder using the Google drive node in the template. 
  Add the InfraNodus API key to the InfraNodus Save to Graph HTTP node 
  Optional: change the name of the graph you want to save the data to in the InfraNodus HTTP node (in the name field of the HTTP post request).
  Run the workflow to ingest all the files and save them into the graph
  Optional: check the link provided in the Step 1 workflow description to see the visualization of your knowledge base. It will look something like that:



  Note:* you can replace the PDF to Text convertor node with a better quality *PDF convertor* from ConvertAPI which respects the original file layout and doesn't split text into small chunks


  Step 2: Chat with your documents

  Deactive the trigger in the Step 1
  Activate the chat trigger in the Step 2
  Add your InfraNodus API credentials to Knowledge Base GraphRAG InfraNodus node
  Optional: change the graph name in the Knowledge Base node to match the name you provided in the step 1 above
  Run the chat and ask the question
  Watch the magic 

  How to use

  You need an InfraNodus GraphRAG API account and key to use this workflow. 

  Create an InfraNodus account
  Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes.

  Requirements

  An InfraNodus account and API key
  An OpenAI (or any other LLM) API key
  A Google Drive OAuth access (follow the n8n instructions)
  Optional: ConvertAPI API key for better quality PDF conversion

  Customizing this workflow

  You can customize this workflow by adding several experts to your AI agent. 

  Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20174217658396-Using-InfraNodus-Knowledge-Graphs-as-Experts-for-AI-Chatbot-Agents-in-n8n

  Also check out the video tutorial with a demo:



  For support and feedback, please, contact us at https://support.noduslabs.com

  To learn more about InfraNodus: https://infranodus.com

nodes_used:
  ["n8n-nodes-base.googleDrive","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleDrive","n8n-nodes-base.switch","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Data Processing"],"complexity":"medium","use_cases":["Chat with documents using graphs","Extract insights from PDFs","Build knowledge graphs for RAG"],"estimated_setup_minutes":15,"required_services":["Google Drive","InfraNodus"],"key_features":["Graph-based RAG without vector stores","Document topic visualization","Gap analysis for research"],"target_audience":["Researchers","Data Engineers"]}


name: ✈️ CO2 emissions of business travels with Carbon Interface API and GPT-4o
author_name: Samir Saci
author_username: samirsaci
categories: []
created_at: 2025-06-07T10:10:06.724Z
updated_at: 2025-06-07T10:10:06.724Z
url: https://n8n.io/workflows/4756
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Tags*: Sustainability, Business Travel, Carbon Emissions, Flight Tracking, Carbon Interface API

  Context

  Hi! I’m Samir, a Supply Chain Engineer and Data Scientist based in Paris, and founder of LogiGreen Consulting.

  I help companies monitor and reduce their environmental footprint by combining AI automation, carbon estimation APIs, and workflow automation.

  This workflow is part of our sustainability reporting initiative, allowing businesses to track the CO₂ emissions of employee flights.

  &gt; Automate carbon tracking for your business travel with AI-powered workflows in n8n!

  📬 For business inquiries, feel free to connect with me on LinkedIn

  Who is this template for?

  This workflow is designed for travel managers, sustainability teams, or finance teams who need to measure and report on emissions from business travel.

  Let’s imagine your company receives a flight confirmation email:



  The AI Agent reads the email and extracts structured data, such as flight dates, airport codes, and number of passengers.

  Then, the Carbon Interface API is called to estimate CO₂ emissions, which are stored in a Google Sheet for sustainability reporting.

  How does it work?

  This workflow automates the end-to-end process of tracking flight emissions from email to CO₂ estimation:

  📨 Gmail Trigger captures booking confirmations  
  🧠 AI Agent extracts structured data (airports, dates, flight numbers)  
  ✈️ Each flight leg is processed individually  
  🌍 Carbon Interface API returns distance and carbon emissions  
  📄 A second Google Sheet node appends the emission data for reporting

  Steps:

  💌 Trigger on new flight confirmation email  
  🧠 Extract structured trip data using AI Agent (flights, airports, dates)  
  📑 Store flight metadata in Google Sheets  
  🧭 For each leg, call the Carbon Interface API  
  📥 Append distance, CO₂ in kg, and timestamp to the flight row  

  What do I need to get started?

  You’ll need:

  A Gmail account receiving SAP Concur or travel confirmation emails  
  A Google Sheet to record trip metadata and CO₂ emissions  
  A free Carbon Interface API key  
  Access to OpenAI for parsing the email via AI Agent  
  A few sample flight confirmation emails to test

  📺 Learn More with n8n Tutorials 

  Get hands-on experience with automation through my comprehensive n8n tutorial playlist, featuring 18+ complete, step-by-step videos and ready-to-use templates.

  Next Steps

  🗒️ Use the sticky notes in the n8n canvas to:

  Add your Gmail and Carbon Interface credentials  
  Send a sample booking email to your inbox  
  Verify that emissions and distances are correctly added to your sheet  

  This template was built using n8n v1.93.0  
  Submitted: June 7, 2025

nodes_used:
  ["n8n-nodes-base.gmailTrigger","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.splitOut","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Sustainability","Data Processing"],"complexity":"medium","use_cases":["track flight emissions","generate sustainability reports","estimate carbon footprint"],"estimated_setup_minutes":30,"required_services":["Carbon Interface API","GPT-4o"],"key_features":["automates CO2 calculation","integrates AI with external APIs","parses structured data from API"],"target_audience":["supply chain engineers","data scientists","sustainability managers"]}


name: 🚚 CO2 emissions of freight shipments with Carbon Interface API and GPT-4o
author_name: Samir Saci
author_username: samirsaci
categories: []
created_at: 2025-06-07T11:02:07.856Z
updated_at: 2025-06-07T11:02:07.856Z
url: https://n8n.io/workflows/4757
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Tags*: Sustainability, Supply Chain, AI Agent, CO2 Emissions, Carbon Interface API, Logistics, Automation

  Context

  Hi! I’m Samir — a Supply Chain Engineer and Data Scientist based in Paris, and founder of LogiGreen Consulting.

  I help logistics teams reduce their environmental footprint by combining AI automation and carbon estimation APIs.

  This workflow is part of our green logistics initiative, allowing businesses to track the CO₂ emissions of last-mile or regional shipments.

  &gt; Automate carbon tracking for shipping operations with n8n!

  📬 For business inquiries, feel free to connect with me on LinkedIn

  Who is this template for?

  This workflow is designed for logistics coordinators, transportation planners, or sustainability officers who want to estimate and record emissions for B2B shipments.

  Let’s imagine your carrier sends a shipment confirmation email after a pickup is scheduled:



  An AI Agent reads the email and extracts structured data: addresses, distance, cargo weight, and delivery time.

  The Carbon Interface API is then called to calculate CO₂ emissions based on weight and distance, and the results are stored in a Google Sheet.

  How does it work?

  This workflow automates the process of tracking CO₂ emissions for scheduled shipments:

  📨 Gmail Trigger captures shipment confirmation emails  
  🧠 AI Agent parses the shipment info (pickup, delivery, weight, distance)  
  🚚 Carbon Interface API estimates CO₂ emissions  
  📊 Google Sheets is used to store shipment metadata and carbon results

  Steps:

  💌 Trigger on new shipment confirmation email  
  🧠 Extract structured shipment info with AI Agent  
  📋 Store metadata in Google Sheets  
  ⚙️ Call Carbon Interface API with weight and distance  
  📥 Append estimated CO₂ emissions to the shipment row

  What do I need to get started?

  You’ll need:

  A Gmail account to receive shipment confirmation emails  
  A Google Sheet to track shipment data and CO₂  
  A free Carbon Interface API key  
  OpenAI access for using the AI Agent parser  
  A few sample emails from your logistics provider to test

  📺 Learn More with n8n Tutorials 

  Get hands-on experience with automation through my comprehensive n8n tutorial playlist, featuring 18+ complete, step-by-step videos and ready-to-use templates.

  Next Steps

  🗒️ Use the sticky notes in the n8n canvas to:

  Add your Gmail and Carbon Interface credentials  
  Try with a sample shipment confirmation email  
  Check your Google Sheet to verify emissions and timestamps

  This template was built using n8n v1.93.0  
  Submitted: June 7, 2025

nodes_used:
  ["n8n-nodes-base.gmailTrigger","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Sustainability","Supply Chain","Logistics"],"complexity":"medium","use_cases":["Calculate shipment CO2 emissions","Track freight carbon footprint","Automate environmental reporting","Integrate carbon data with AI insights"],"estimated_setup_minutes":15,"required_services":["Carbon Interface API","OpenAI (GPT-4o)","Google Sheets","Airtable"],"key_features":["API integration for carbon estimation","AI-driven emissions analysis","Automated data logging to spreadsheets","Custom message generation for sustainability reports"],"target_audience":["Supply Chain Engineers","Sustainability Managers","Logistics Analysts"]}


name: Perplexity-Style Iterative Research with Gemini and Google Search
author_name: slow-groovin@api2o.com
author_username: coze
categories: []
created_at: 2025-06-07T15:02:56.126Z
updated_at: 2025-06-07T15:02:56.126Z
url: https://n8n.io/workflows/4758
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  AI Comprehensive Research on User's Query with Gemini and Web Search

  What is this?
  Perform comprehensive research on a user's query by dynamically generating search terms, querying the web using Google Search (by Gemini) , reflecting on the results to identify knowledge gaps, and iteratively refining its search until it can provide a well-supported answer with citations. (like Perplexity)

  This workflow is a reproduction of gemini-fullstack-langgraph-quickstart in N8N.

  The gemini‑fullstack‑langgraph‑quickstart is a demo by the Google‑Gemini team that showcases how to build a powerful full‑stack AI agent using Gemini and LangGraph

  How It Works

  Generate Query 💬
  generates one or more search queries tasks based on the User's question.
  uses Gemini 2.0 Flash

  Web Research 🌐
  execute web search tasks using the native Google Search API tool in combination with Gemini 2.0 Flash.

  Reflection 📚
  Identifies knowledge gaps and generates potential follow-up queries. 

  Setup

  Configure API Credentials:
     Create Google Gemini(PaLM) Api Credential using you own Gemini key
     Connect the credential with three nodes: Google Gemini Chat Model and GeminiSearch and reflection

  Configure Redis Source:
     prepare a Redis service that can be accessed by n8n
     Create Redis Crediential and connect it with all Redis node

  Customize

  Try using different Gemini models.
  Try modifying the parameters number_of_initial_queries and max_research_loops.

  Why use Redis?

  Use Redis as an external storage to maintain global variables (counter, search results, etc.)

  This workflow contains a loop process, which need global variables (as State in LangGraph).

  It is difficult to achieve global variables management without external storage in n8n.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.splitOut","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.aggregate","n8n-nodes-base.redis","n8n-nodes-base.redis","n8n-nodes-base.redis","n8n-nodes-base.redis","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.redis","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.redis","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.redis","n8n-nodes-base.redis","n8n-nodes-base.merge","n8n-nodes-base.redis","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 13396 characters]

metadata_json:
  {"categories":["AI/ML","Data Processing"],"complexity":"medium","use_cases":["conduct iterative web research","generate dynamic search queries","analyze search results for gaps","provides cited answers"],"estimated_setup_minutes":15,"required_services":["Google Gemini","Google Search API","Redis"],"key_features":["iterative query refinement","knowledge gap detection","citation-based responses","dynamic search term generation","result aggregation"],"target_audience":["researchers","data analysts","AI developers"]}


name: Send Cryptocurrency Price Threshold Alerts from CoinGecko to Discord
author_name: LukaszB
author_username: lukaszb
categories: []
created_at: 2025-06-07T16:24:49.130Z
updated_at: 2025-06-07T16:24:49.130Z
url: https://n8n.io/workflows/4759
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Crypto Price Alert – n8n Workflow

  A simple and effective crypto alert system for anyone who wants to stay up to date with coin price changes — without refreshing charts all day. This workflow checks the current price of your chosen cryptocurrency (via CoinGecko) and sends you an alert on Discord if it goes above or below your target range.

  It’s lightweight, easy to set up, and runs on autopilot.

  What the Workflow Does
  Checks the live price of a selected coin using the CoinGecko API.
  Compares it to the max/min prices you define manually.
  Decides if the price is too high or too low.
  Sends an alert message to Discord depending on the result.

  How It Works
  The flow is triggered manually or on a schedule (your choice).
  It pulls the current price of the coin you set.
  Compares that price with your min and max values.
  Sends a “high” or “low” message to your Discord webhook.

  Setup Steps
  Enter your coin ID and price thresholds in the “Set Low and High” node.
  Paste your Discord webhook URLs in the "Message High" and "Message Low" nodes.
  Optional: Adjust the schedule trigger to run every X minutes/hours.
  Run once manually to test — takes under 1 minutes.

  Full instructions and config tips are in sticky notes inside the workflow.

nodes_used:
  ["n8n-nodes-base.coinGecko","n8n-nodes-base.manualTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.discord","n8n-nodes-base.discord","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Cryptocurrency","Communication"],"complexity":"simple","use_cases":["monitor crypto prices","send price alerts","track market changes"],"estimated_setup_minutes":5,"required_services":["CoinGecko","Discord"],"key_features":["threshold-based alerting","scheduled monitoring","custom price ranges"],"target_audience":["traders","crypto enthusiasts","devops engineers"]}


name: Gmail Customer Support Auto-Responder with Ollama LLM and Pinecone RAG
author_name: Aashit Sharma
author_username: aashitsharma
categories: []
created_at: 2025-06-07T17:27:27.416Z
updated_at: 2025-06-07T17:27:27.416Z
url: https://n8n.io/workflows/4760
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Gmail Customer Support Auto-Responder with Ollama LLM and Pinecone RAG

  Built by Setidure Technologies  
  Automate intelligent, friendly replies to customer queries using AI, vector search, and Gmail — all without human effort.

  Overview

  This is a ready-to-deploy smart customer support automation template for businesses that want to reply to emails instantly and accurately with the warmth of a human agent.  

  It uses Gmail, LangChain agents, Ollama-hosted LLMs, and Pinecone vector search to craft contextual, brand-aligned replies at scale.

  &gt; Note: This template uses community nodes and requires a self-hosted n8n instance.

  What the Workflow Does

  1. Triggers on Incoming Emails  
  Uses Gmail Trigger node to listen for new messages  
  Activates every minute to ensure fast responses

  2. Classifies Email Intent  
  A LangChain Text Classifier detects whether the email is a Customer Support query  
  Non-relevant emails are skipped

  3. Generates AI Response  
  An AI Agent powered by Ollama generates the email reply  
  Follows a predefined tone: "Mr. Aashit Sharma from Setidure Technologies"  
  Written in a warm, human tone with natural phrasing

  4. Retrieves FAQ-Based Knowledge  
  Connects to Pinecone vector database for real-time FAQ retrieval  
  Enhances responses with specific, accurate product or policy information

  5. Labels Email in Gmail  
  Automatically tags emails with labels like Handled or Auto-Replied for easy tracking

  6. Sends Email Reply  
  Sends the generated response back to the customer  
  Includes personal sign-off and clean formatting

  Tech Stack Used

  Gmail Trigger & Send Nodes  
  LangChain AI Agent & Classifier  
  Ollama LLMs (e.g., phi4, llama3)  
  Pinecone Vector Store  
  Custom Prompts for Brand Persona  
  Local Embeddings using Ollama

  Key Features

  Fully automated — no human action needed  
  Local LLMs ensure data privacy  
  Real-time answers powered by vector search  
  Brand-personality aligned tone  
  Organized inbox with Gmail labels

  Best For

  Startups scaling support with limited staff  
  SaaS companies or e-commerce businesses  
  Privacy-conscious enterprises using local LLMs  
  Teams building branded auto-communication workflows

  Customization Tips

  Modify AI prompt to reflect your brand's voice and tone  
  Expand classifier for more email categories  
  Replace Gmail output with Slack, Notion, or your CRM  
  Update Pinecone FAQ index to match evolving support content

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.gmailTrigger","@n8n/n8n-nodes-langchain.textClassifier","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.vectorStorePinecone","n8n-nodes-base.gmail","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.lmOllama","@n8n/n8n-nodes-langchain.embeddingsOllama","@n8n/n8n-nodes-langchain.lmChatOllama","@n8n/n8n-nodes-langchain.memoryBufferWindow"]

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metadata_json:
  {"categories":["Customer Support","AI/ML","Communication"],"complexity":"medium","use_cases":["automate email responses","extract customer intent","search knowledge base","generate empathetic replies"],"estimated_setup_minutes":20,"required_services":["Gmail","Pinecone","Ollama"],"key_features":["LLM-based response generation","Vector database RAG","Sentiment analysis","Context-aware memory"],"target_audience":["support agents","business analysts","frontend devs"]}


name: AI-Powered Interview Preparation System using Local LLM for Campus Placements
author_name: Aashit Sharma
author_username: aashitsharma
categories: []
created_at: 2025-06-07T17:37:22.442Z
updated_at: 2025-06-07T17:37:22.442Z
url: https://n8n.io/workflows/4761
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Overview
  An AI-powered, end-to-end interview preparation and mentoring automation system for campus placements. It enables placement cells to generate hyper-personalized 4-page interview preparation PDFs for shortlisted students, by combining job descriptions (JDs), candidate data, and LLMs via LangChain and Ollama.

  Note: This template requires self-hosted n8n to run community nodes like LangChain and Ollama.

  What This Workflow Does
  Accepts a CSV of shortlisted students and a JD via form upload

  Analyzes student profile vs JD using Ollama LLM via LangChain

  Generates personalized interview preparation PDFs

  Sends the PDF to each student via email

  Logs all data in Google Sheets and prevents duplicate processing

  Workflow Preview
  📷 Please add a workflow screenshot here showing the main nodes and flow

  Step-by-Step Flow
  1. Form Submission
  CSV of shortlisted students + JD + company name is submitted via HTTP Request form trigger.

  2. Data Parsing and Google Sheet Logging
  CSV parsed → structured rows added to Google Sheet named with company + batch.

  3. Candidate Filtering
  Only students with N8N_Agent = Not Generated are selected to avoid reprocessing.

  4. AI-Powered Report Generation
  LangChain agent (via Ollama + Gemini Search Tool) generates a 4-page Markdown report:

  Page 1: Profile Summary, Skill Gap Analysis, Company Insights

  Page 2: 15–20 Personalized Interview Questions

  Page 3: 5 Group Discussion Topics + Strategy

  Page 4: Custom Preparation Plan + Suggested Resources

  5. PDF Creation
  Markdown → Stylish PDF via APITemplate.io

  6. Email Delivery
  Each student receives a personalized email with the attached report.

  7. Google Sheet Status Update
  Marks the student’s row as “Generated” in N8N_Agent column.

  Prerequisites
  Self-hosted n8n with Community Nodes enabled

  Local or Docker-hosted Ollama with LLaMA3.2 or equivalent model

  Activated LangChain and Gemini Search Tool nodes

  APITemplate.io API Key

  Connected Google Sheets account

  SMTP setup or Gmail node for email delivery

  Customization Tips
  Replace the LLM prompt in the LangChain node with your own tone/style

  Modify the PDF template on APITemplate.io to reflect your institution branding

  Update the email copy for formal or informal tones

  Add new filters (e.g., minimum CGPA, branch) for student selection

nodes_used:
  ["n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.lmChatOllama","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.lmChatOllama","n8n-nodes-gemini-search.geminiSearchToolTool","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.formTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.extractFromFile","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.apiTemplateIo","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.emailSend","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Education","HR & Recruitment","AI/ML"],"complexity":"medium","use_cases":["Generate personalized interview prep materials","Automate student assessment","Create hyper-personalized PDFs for placement readiness"],"estimated_setup_minutes":30,"required_services":["Ollama","Gemini","CSV Parser","PDF Generator"],"key_features":["Integration with Local LLM via Ollama","Automated PDF generation from job descriptions and candidate data","Hyper-personalized content creation using LangChain"],"target_audience":["Placement coordinators"]}


name: Automate Sleep Meditation Content Creation with ElevenLabs V3 & DeepSeek AI
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-07T17:46:27.155Z
updated_at: 2025-06-07T17:46:27.155Z
url: https://n8n.io/workflows/4762
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Automate the production of ad-friendly meditation content—from trend research to AI voiceover generation.
  🌟 Key Features

      Style-Specific Content Generation

          Input a meditation style (e.g., "calming," "motivational") and generate tailored scripts.

          Customize voice profiles using ElevenLabs.

      Trend-Based Title Research

          Scrape YouTube/Brave Search for popular video titles in your niche.

          Remove duplicates, filter explicit content, and aggregate results.

      AI-Powered Content Creation

          Generate fresh video titles using aggregated trends.

          Create 2500-character voiceover scripts with pacing cues (e.g., [sighs], ... pauses).

      Structured Output Validation

          Auto-fix malformed AI outputs with recursive parsing.

          Enforce script constraints (no line breaks/comments).

      Audio Production & Storage

          Convert scripts to lifelike speech via ElevenLabs.

          Auto-save audio to Google Drive with timestamps.

  🛠️ Nodes Used

      Data Prep: Brave Search → SplitOut → Remove Duplicates → Text Classifier (explicit filter)

      AI Models: DeepSeek (title/script generation), Output Parsers (schema validation)

      TTS: ElevenLabs (voice synthesis) → Google Drive (storage)

      Utilities: Webhook trigger, Code node (input validation), Sticky Notes (instructions)

  💡 Use Cases

      Create ASMR/sleep meditation content at scale.

      Repurpose trending topics into new videos.

      Generate voiceovers for faceless YouTube channels.

  🔗 Setup Notes

      Required APIs:

          ElevenLabs (voice synthesis)

          Brave Search (video trends)

          Google Drive (storage)

      Input: Send style (e.g., "sleep meditation") and voice_id to the webhook.

      Output: MP3 audio + metadata saved to Google Drive.

  📌 Pro Tips

      Use output parsers to enforce JSON schemas and avoid malformed AI responses.

      Attach royalty-free visuals using the included background video.

  Extend with video composition orthumbnail generation workflows.

      ✅ Ad-Friendly: Filters explicit titles and enforces YouTube-safe content guidelines.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatDeepSeek","n8n-nodes-base.splitOut","n8n-nodes-base.aggregate","n8n-nodes-base.removeDuplicates","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.textClassifier","@brave/n8n-nodes-brave-search.braveSearch","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.outputParserStructured","@elevenlabs/n8n-nodes-elevenlabs.elevenLabs","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Content Generation"],"complexity":"medium","use_cases":["generate meditation scripts","create ad-friendly content","customise AI voiceovers","research trending titles"],"estimated_setup_minutes":15,"required_services":["ElevenLabs","DeepSeek"],"key_features":["style-specific script generation","voice profile customisation","trending title research","ad-friendly formatting"],"target_audience":["creators","content marketers","mental health professionals"]}


name: Extract Invoice Data from PDFs with AI - Google Sheets Email Alerts
author_name: Aashit Sharma
author_username: aashitsharma
categories: []
created_at: 2025-06-07T17:49:24.951Z
updated_at: 2025-06-07T17:49:24.951Z
url: https://n8n.io/workflows/4763
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Built by Setidure Technologies
  This smart n8n automation extracts invoice details from PDF files uploaded to Google Drive using AI, logs them to a Google Sheet, and notifies the billing team via email — all without manual intervention.

  ⚠️ Note: This workflow requires a self-hosted n8n instance with LangChain, LLM, and Google integrations configured.

  📦 What This Workflow Does
  Monitors a Google Drive folder for new invoice uploads

  Extracts text and parses key invoice details using LLM via LangChain

  Logs extracted data into a Google Sheet (Invoice Database)

  Generates a summary email using GPT-4O-MINI (Greenie)

  Sends the email to the billing team via Gmail

  ✅ Prerequisites
  A Google Drive folder to monitor for PDF uploads

  A Google Sheet named Invoice Database with the following columns:

  Invoice Number, Client Name, Client Email, Client Address, Client Phone, Invoice Date, Due Date, Total Amount

  Service account or OAuth credentials for:

  Google Drive

  Google Sheets

  Gmail

  LangChain + Ollama integration for LLM responses

  🔧 Step-by-Step Setup Instructions
  Clone this workflow into your self-hosted n8n instance

  Set up credentials:

  Google Drive (for folder trigger)

  Google Sheets (for data logging)

  Gmail (for sending email)

  Ollama (local LLM) or any connected LangChain provider

  Configure the trigger node to watch your specific Invoice Uploads folder

  Update the Google Sheet node with your Invoice Database sheet URL and column mapping

  Test with a sample invoice to validate the AI extraction and email generation

  🔄 Workflow Steps
  Step 1: Trigger on New File in Google Drive
  Node Name: Watch for New Invoices
  Type: Google Drive Trigger

  Event: fileCreated

  Triggers when a new PDF file is uploaded to a designated folder

  Step 2: Download the Uploaded File
  Node Name: Download Invoice PDF
  Type: Download Binary

  Downloads the invoice file from Google Drive

  Step 3: Extract Raw Text from PDF
  Node Name: Extract PDF Text
  Type: Extract from File

  Extracts unstructured text content from the downloaded PDF

  Step 4: Parse Invoice Fields Using AI
  Node Name: Parse Invoice Data with LLM
  Type: LangChain Agent

  LLM is prompted to extract:

  Invoice Number

  Client Name, Email, Address, Phone

  Invoice Date, Due Date, Total Amount

  Fields not found are skipped

  Step 5: Log Extracted Data to Google Sheet
  Node Name: Log to Invoice Database
  Type: Google Sheets

  Appends a new row with the extracted fields to the Invoice Database spreadsheet

  Step 6: Create Email Notification via LLM
  Node Name: Generate Billing Email Summary
  Type: LangChain Agent (GPT-4O-MINI)

  Prompt instructs AI to:

  Act as “Greenie” from Green Grass Corp

  Inform billing that a new invoice was processed

  Confirm logging into the Invoice Database

  Step 7: Send the Email to Billing Team
  Node Name: Email Billing Team
  Type: Gmail Send

  To: billing@example.com

  Subject and body injected from LLM output

  Step 8: End Workflow Gracefully
  Node Name: End
  Type: No Operation

  Used to cleanly terminate the flow

  🧠 Example Output (Email)

  Subject: New Invoice Logged – Client: ABC Corp

  Hi Billing Team,

  A new invoice has been received and processed automatically. The following details have been extracted and logged into the Invoice Database:

  Invoice Number: INV-1024  
  Client: ABC Corp  
  Amount: $1,450  
  Due Date: July 15, 2025  

  Please review the Invoice Database for full details.

  Regards,  
  Greenie  
  Green Grass Corp

nodes_used:
  ["@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.gmail","n8n-nodes-base.noOp","@n8n/n8n-nodes-langchain.lmOllama","@n8n/n8n-nodes-langchain.vectorStorePGVector","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets"]

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metadata_json:
  {"categories":["Finance","Data Processing"],"complexity":"medium","use_cases":["extract invoice details from PDF files","automate billing data entry","send automated email notifications","log invoice data to spreadsheets"],"estimated_setup_minutes":18,"required_services":["Google Drive","Google Sheets","Ollama (AI Models)","PGVector (Vector Database)"],"key_features":["AI-powered invoice data extraction","PDF text parsing using LLM","automated email alerts","manual data entry eliminated"],"target_audience":["finance managers","billing specialists","accountants"]}


name: 🌐 Firecrawl Website Content Extractor
author_name: Aashit Sharma
author_username: aashitsharma
categories: []
created_at: 2025-06-07T17:56:19.339Z
updated_at: 2025-06-07T17:56:19.339Z
url: https://n8n.io/workflows/4764
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  🌐 Firecrawl Website Content Extractor (n8n Workflow)

  This n8n automation workflow uses Firecrawl API to extract structured data (e.g., quotes and authors) from web pages — such as Quotes to Scrape — and handles retries in case of delayed extraction.

  🔁 Workflow Overview

  🎯 Purpose:
  Crawl and extract structured web data using Firecrawl
  Wait for asynchronous scraping to complete
  Retrieve and validate results
  Support retries if content is not ready

  🔧 Step-by-Step Node Breakdown

  1. 🧪 Manual Trigger
  Node: When clicking ‘Test workflow’
  Used to manually test or execute the workflow during setup or debugging.

  2. 📤 Firecrawl Extract API Request
  Node: Extract
  Sends a POST request to https://api.firecrawl.dev/v1/extract
  Payload includes:
    urls: List of pages to crawl (https://quotes.toscrape.com/*)
    prompt: "Extract all quotes and their corresponding authors from the website."
    schema: JSON schema defining expected structure (quotes[], each with text and author)

  &gt; 📌 Uses an HTTP Header Auth credential for Firecrawl API

  3. ⏱️ Wait for 30 Seconds
  Node: 30 Secs
  Gives Firecrawl time to finish processing in the background
  Prevents hitting the API before results are ready

  4. 📥 Get Results
  Node: Get Results
  Performs a GET request to the status URL using {{ $('Extract').item.json.id }} to retrieve extraction results.

  5. ✅❌ Condition Check
  Node: If
  Checks if the data array is empty (i.e., no results yet)
  If data is empty:
    Waits 10 more seconds and retries
  If data is available:
    Passes data to the next step (e.g., processing or storage)

  6. 🔁 Retry Delay
  Node: 10 Seconds
  Waits briefly before sending another GET request to Firecrawl

  7. 🛠️ Edit Fields (Optional Output Formatting)
  Node: Edit Fields
  Placeholder to structure or format the extracted results (quotes and authors)

  🧾 Sticky Note: Firecrawl Setup Guide

  Included as an embedded reference:
  🔗 10% Firecrawl Discount
  🧰 Instructions to:
    Add Firecrawl API credentials in n8n
    Use Firecrawl Community Node for self-hosted instances
    Set up the schema and prompt for targeted data extraction

  ✅ Key Features

  🔌 API-based crawling with schema-structured output
  ⏱️ Smart waiting + retry mechanism
  🧠 AI prompt integration for intelligent data parsing
  ⚙️ Flexible for different URLs, prompts, and schemas

  📦 Sample Output Schema

  {
    "quotes": [
      {
        "text": "The world as we have created it is a process of our thinking. It cannot be changed without changing our thinking.",
        "author": "Albert Einstein"
      },
      {
        "text": "It is our choices, Harry, that show what we truly are, far more than our abilities.",
        "author": "J.K. Rowling"
      }
    ]
  }

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.set"]

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metadata_json:
  {"categories":["Data Processing","AI/ML"],"complexity":"medium","use_cases":["extract structured web data","scrape quotes from pages","handle asynchronous scraping","retry failed requests"],"estimated_setup_minutes":15,"required_services":["Firecrawl"],"key_features":["asynchronous web scraping","content validation","automatic retry logic","structured data extraction"],"target_audience":["data analysts","developers","content aggregators"]}


name: Generate & Optimize Brand Stories with Ollama LLMs and Google Sheets
author_name: Aashit Sharma
author_username: aashitsharma
categories: []
created_at: 2025-06-07T18:10:54.173Z
updated_at: 2025-06-07T18:10:54.173Z
url: https://n8n.io/workflows/4765
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Overview
  This n8n automation template allows marketers, branding teams, and creative professionals to auto-generate, evaluate, and iteratively optimize brand stories using Ollama-hosted LLMs and LangChain agents. Each story is refined until it meets quality criteria and is then saved to Google Sheets for publishing or reuse.

  ⚠️ Note: This template uses community nodes and requires a self-hosted n8n instance with LangChain and Ollama integrations.

  What the Workflow Does
  Receives a chat-triggered brand story request

  Guides the user to generate a structured brand story

  Evaluates the story for tone, uniqueness, quote inclusion, and emoji removal

  Loops through optimization until the story is finalized

  Saves the final story to Google Sheets

  Target Users
  Startup founders

  Brand consultants

  Social media strategists

  Marketers building bios, taglines, intros

  Step-by-Step Setup Instructions
  Setup Prerequisites

  Install self-hosted n8n with LangChain and Ollama nodes

  Load phi4-mini and qwen3:4b models into your local Ollama instance

  Create a Google Sheet with a sheet named BrandStories and columns:

  Name

  Final Story

  Timestamp

  Trigger Configuration

  Set up the Chat Trigger node (@n8n/n8n-nodes-langchain.chatTrigger) with webhook ID:
  fab30ad7-8a5a-4477-be98-1aa43b92b052

  Customize Prompts

  Update the Brand Storytelling Agent prompt to reflect your brand tone or story format

  Optionally refine the Evaluator Agent criteria (e.g., enforce industry tone)

  Google Sheets Setup

  Use your Google Sheets OAuth2 credentials

  Map fields to Name, Final Story, and Timestamp columns

  Run the Flow

  On new chat input, the system auto-generates a brand story

  It loops between Evaluator and Optimizer agents until the output is labeled "Finished"

  Final output is saved to your Google Sheet

  Flowchart (mermaid)
  mermaid
  Copy
  Edit
  flowchart TD
      A[Chat Trigger: New Message] --&gt; B[Brand Storytelling Agent]
      B --&gt; C[Set Bio Variable]
      C --&gt; D[Evaluator Agent]
      D --&gt; E{Is Output "Finished?"}
      E -- Yes --&gt; F[Save Brand Story to Sheets]
      E -- No --&gt; G[Optimizer Agent]
      G --&gt; H[Update Bio Variable]
      H --&gt; D

  Credentials Used
  Google Sheets OAuth2 for storage

  Ollama API (local models phi4-mini and qwen3:4b)

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOllama","@n8n/n8n-nodes-langchain.lmChatOllama","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if"]

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metadata_json:
  {"categories":["Marketing","AI/ML"],"complexity":"medium","use_cases":["generate brand stories","optimize narrative content","evaluate and refine text","save content to spreadsheets"],"estimated_setup_minutes":30,"required_services":["Google Sheets","Ollama"],"key_features":["iterative content refinement","quality criteria evaluation","LangChain agent orchestration","self-hosted LLM integration"],"target_audience":["marketers","creative professionals","content managers"]}


name: Automate LinkedIn Posts with Claude AI, DALL-E Images & Google Sheets Approval
author_name: Usman Liaqat
author_username: usmanliaqat
categories: []
created_at: 2025-06-07T18:34:34.273Z
updated_at: 2025-06-07T18:34:34.273Z
url: https://n8n.io/workflows/4766
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  How it works

  This workflow automates your entire LinkedIn content strategy, from ideation to publishing.

  Daily Idea Generation:** Every day, the workflow uses an advanced AI agent (Anthropic's Claude model) to generate a new, viral-optimized LinkedIn post idea, complete with a title, full text, and a detailed image description. It analyzes your past posts from a Google Sheet to ensure content is fresh and aligns with one of your four content pillars: timeless principles, case studies, growth hacks, or controversial ads.
  AI Image Creation:** It then uses OpenAI's DALL-E to create a custom, high-quality image based on the generated description and a style reference image you provide, ensuring brand consistency.
  Review & Approval Workflow:** The generated post and its accompanying image are automatically saved as a new row in a Google Sheet, marked with a "review" status. This gives you full editorial control.
  Automated Publishing:** Once you approve a post by changing its status to "ready" in the Google Sheet, a separate part of the workflow picks it up and automatically publishes it to your LinkedIn profile at a scheduled time.
  Status Tracking:** After publishing, the workflow updates the status in your Google Sheet to "posted," so you always have a clear overview of your content pipeline.

  Set up steps

  This workflow integrates several services. Follow these steps to get it running:

  Copy the Google Sheet: Make a copy of the AI Posts Content Machine Google Sheet template and select your copy in the Get Past Ideas, Save Post, Get Ready Posts, and Update Status nodes.
  Set Up Credentials: You will need to create and add API credentials for the following services within the corresponding n8n nodes:
      Google Sheets & Google Drive: Create a Google credential.
      Anthropic: Add your API key in the Anthropic Chat Model node.
      OpenAI: Add your API key as a Header Auth credential in the OpenAI Image node.
      Perplexity AI: Add your API key as a Header Auth credential inside the Perplexity Research sub-workflow.
      LinkedIn: Create a LinkedIn credential.
  Customize Your Content:
      In the Idea Generator node, adjust the system prompt to reflect your specific audience, topics, and content style.
      Create a folder in Google Drive for your post images. Add a reference image to this folder that defines your desired visual style.
      Paste the shareable link to your style reference image into the Image Style node.
  Activate the Workflow: Enable the workflow to start the automated content creation and publishing process.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatAnthropic","n8n-nodes-base.convertToFile","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.limit","n8n-nodes-base.stickyNote","n8n-nodes-base.twitter","n8n-nodes-base.set","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.wait","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.googleDrive","n8n-nodes-base.linkedIn","n8n-nodes-base.googleSheets","n8n-nodes-base.perplexityTool"]

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metadata_json:
  {"categories":["Marketing","Communication","AI/ML"],"complexity":"medium","use_cases":["automate social media content","generate post ideas","create images for posts","approve content in spreadsheets"],"estimated_setup_minutes":30,"required_services":["Google Sheets","DALL-E","Google Drive","LinkedIn"],"key_features":["AI-driven content ideation","automated image generation","collaborative approval workflow","scheduled publishing","content pillar alignment"],"target_audience":["marketers","social media managers","content creators"]}


name: VEO3 Video Generator with AI Optimization and Google Drive Storage
author_name: Friedemann Schuetz
author_username: freddy-schuetz
categories: []
created_at: 2025-06-07T18:34:44.834Z
updated_at: 2025-06-07T18:34:44.834Z
url: https://n8n.io/workflows/4767
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:19
description:
  Welcome to my VEO3 Video Generator Workflow!

  This automated workflow transforms simple text descriptions into professional 8-second videos using Google's cutting-edge VEO3 AI model. Users submit video ideas through a web form, and the system automatically generates optimized prompts, creates high-quality videos with native audio, and delivers them via Google Drive - all powered by Claude 4 Sonnet for intelligent prompt optimization.

  This workflow has the following sequence:
  VEO3 Generator Form - Web form interface for users to input video content, format, and duration
  Video Prompt Generator - AI agent powered by Claude 4 Sonnet that:
     Analyzes user input for video content requirements
     Creates factual, professional video titles
     Generates detailed VEO3 prompts with subject, context, action, style, camera motion, composition, ambiance, and audio elements
     Optimizes prompts for 16:9 landscape format and 8-second duration
  Create VEO3 Video - Submits the optimized prompt to fal.ai VEO3 API for video generation
  Wait 30 seconds - Initial waiting period for video processing to begin
  Check VEO3 Status - Monitors the video generation status via fal.ai API
  Video completed? - Decision node that checks if video generation is finished
     If not completed: Returns to wait cycle
     If completed: Proceeds to video retrieval
  Get VEO3 Video URL - Retrieves the final video download URL from fal.ai
  Download VEO3 Video - Downloads the generated MP4 video file
  Merge - Combines video data with metadata for final processing
  Save Video to Google Drive - Uploads the video to specified Google Drive folder
  Video Output - Displays completion message with Google Drive link to user

  The following accesses are required for the workflow:
  Anthropic API** (Claude 4 Sonnet): Documentation
  Fal.ai API** (VEO3 Model): Create API key at https://fal.ai/dashboard/keys
  Google Drive API**: Documentation

  Workflow Features:
  User-friendly web form**: Simple interface for video content input
  AI-powered prompt optimization**: Claude 4 Sonnet creates professional VEO3 prompts
  Automatic video generation**: Leverages Google's VEO3 model via fal.ai
  Status monitoring**: Real-time tracking of video generation progress
  Google Drive integration**: Automatic upload and sharing of generated videos
  Structured output**: Consistent video titles and professional prompt formatting
  Audio optimization**: VEO3's native audio generation with ambient sounds and music

  Current Limitations:
  Format**: Only 16:9 landscape videos supported
  Duration**: Only 8-second videos supported
  Processing time**: Videos typically take 60-120 seconds to generate

  Use Cases:
  Content creation**: Generate videos for social media, websites, and presentations
  Marketing materials**: Create promotional videos and advertisements
  Educational content**: Produce instructional and explanatory videos
  Prototyping**: Rapid video concept development and testing
  Creative projects**: Artistic and experimental video generation
  Business presentations**: Professional video content for meetings and pitches

  Feel free to contact me via LinkedIn, if you have any questions!

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.form","n8n-nodes-base.formTrigger","n8n-nodes-base.stickyNote"]

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name: Turn Monoprix Delivery Emails into Calendar Events using ChatGPT and Google Calendar
author_name: Mathieu Romary
author_username: mathi3u
categories: []
created_at: 2025-06-08T06:13:49.811Z
updated_at: 2025-06-08T06:13:49.811Z
url: https://n8n.io/workflows/4771
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Intro:
  The purpose of this workflow is to simply convert you planned Grocery delivery  confirmation email to a Google Calendar event in your family calendar. While based on a Monoprix.fr email format, it is applicable/adaptable to almost anything else. 

  How it works:
  It is triggered by reception of the confirmation email on your Gmail. The workflow then extracts relevant data using ChatGPT, formats it, and creates a Google Calendar event. 

  Steps to use it:
  Import template in your n8n
  Update credentials for Gmail, Google Calendar, and ChatGPT
  Test workflow based on confirmation email received
  Activate workflow

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.set","n8n-nodes-base.googleCalendar","n8n-nodes-base.gmailTrigger","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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  {"categories":["Communication","Data Processing"],"complexity":"simple","use_cases":["convert emails to calendar events","extract data from delivery emails","automate grocery delivery scheduling","parse email headers and bodies"],"estimated_setup_minutes":10,"required_services":["Google Calendar","Gmail","ChatGPT"],"key_features":["AI-powered email parsing","automatic event creation","flexible input adapter","family calendar integration"],"target_audience":["personal users","families"]}


name: Automated Airtable to Postgres Migration with n8n
author_name: Zacharia Kimotho
author_username: imperolq
categories: []
created_at: 2025-06-08T06:31:28.007Z
updated_at: 2025-06-08T06:31:28.007Z
url: https://n8n.io/workflows/4772
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Overview

  This ETL system automates the process of migrating data from Airtable to PostgreSQL with a single API request.

  It maps your Airtable schema into a Postgres-compatible structure.
  Automatically creates new tables in your Postgres database.
  Migrates all the data while preserving formats and relationships.

  &gt; ⚙️ Originally built in-house to help us migrate off Airtable after exceeding usage limits.

  🔧 How It Works

  Accepts Airtable and Postgres credentials via HTTP requests.
  Authenticates both services and validates schema compatibility.
  Fetches data from Airtable and maps each table and field to PostgreSQL equivalents.
  Creates the necessary tables in your Postgres database.
  Inserts all records in batches.
  Returns a success response with summary stats.

  &gt; Bonus operations: You can list or delete created tables using API endpoints.

  Setup Instructions (n8n Workflow)

  Step 1: Airtable Configuration

  Generate an Airtable access token from the Airtable developer hub.
  Copy your Base ID or URL.

  Step 2: PostgreSQL Configuration

  Gather your PostgreSQL connection details:

    Host
    Port
    Database name
    Username
    Password

  Step 3: Deploy in n8n

  Import the workflow into your n8n instance.
  Use a simple HTTP request tool like curl or Postman to trigger migration actions.

  API Endpoints & Payloads

  Here are the available HTTP endpoints and how to use them.

  1. Test Airtable Credentials

  curl -X POST "https://n8n.com/webhook/123/validate-airtable" \
    -H "Content-Type: application/json" \
    -d '{
      "airtable": {
        "airtableId": "app12345",
        "airtableToken": "pjhy.iyhhs"
      }
    }'

  2. Test PostgreSQL Credentials

  curl -X POST "https://n8n.com/webhook/123/validate-postgres" \
    -H "Content-Type: application/json" \
    -d '{
      "postgres": {
        "host": "aws-0-us-west-1.pooler.supabase.com",
        "port": "6543",
        "user": "postgres.username",
        "password": "gamjgnrkxetb",
        "database": "postgres"
      }
    }'

  3. Sync Airtable Data to Postgres

  curl -X POST "https://n8n.com/webhook/123/sync" \
    -H "Content-Type: application/json" \
    -d '{
      "host": "aws-0-us-west-1.pooler.supabase.com",
      "port": "6543",
      "user": "postgres.username",
      "password": "gamjgnrkxetb",
      "database": "postgres",
      "airtableId": "app73PqALbM3AM0xN",
      "airtableToken": "patNCueRkrLI98fEq.9ae7f9786e9ad73ac21ca26d8046f08ad77e135ae950a6e2ff3760d85aca3db4",
      "action": "Move"
    }'

  Expected Response:

  [
    {
      "statusCode": 200,
      "statusMessage": "Data migration successful",
      "recordsProcessed": 152,
      "tablesProcessed": 3
    }
  ]

  4.List All Created Tables

  curl -X POST "https://n8n.com/webhook/123/list-tables" \
    -H "Content-Type: application/json" \
    -d '{
      "postgres": {
        "host": "aws-0-us-west-1.pooler.supabase.com",
        "port": "6543",
        "user": "postgres.username",
        "password": "gamjgnrkxetb",
        "database": "postgres"
      }
    }'

  5. Delete Migrated Tables

  curl -X POST "https://n8n.com/webhook/123/delete-tables" \
    -H "Content-Type: application/json" \
    -d '{
      "postgres": {
        "host": "aws-0-us-west-1.pooler.supabase.com",
        "port": "6543",
        "user": "postgres.username",
        "password": "gamjgnrkxetb",
        "database": "postgres"
      }
    }'

  Technical Notes

  Schema Mapping**: Field types from Airtable are mapped to PostgreSQL equivalents (e.g. singleLineText → VARCHAR, number → INTEGER, checkbox → BOOLEAN, etc.).
  Linked Records**: Relationships in Airtable bases are resolved and converted into foreign key-friendly formats.
  Batch Inserts**: Records are inserted in optimized chunks to improve performance and avoid payload limits.
  Error Handling**: Invalid credentials, schema mismatches, or connection issues will return proper HTTP status codes and error messages.

  Usage Scenarios

  Airtable to Postgres migration during scale-up.
  Backup or sync Airtable records to a SQL environment.
  Use Postgres-powered dashboards while editing in Airtable.

  Requirements

  Airtable Pro/Developer Account
  PostgreSQL database (e.g. Supabase, Render, or local instance)
  n8n instance with webhook exposure
  Basic familiarity with HTTP requests (curl, Postman, or integrations)

  Need Help?

  Feel free to reach out via LinkedIn or Email if you need help adapting this workflow for your organization or extending it with extra transformations.

  Happy productivity!

nodes_used:
  ["n8n-nodes-base.splitInBatches","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.limit","n8n-nodes-base.splitInBatches","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.limit","n8n-nodes-base.set","n8n-nodes-base.splitInBatches","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.html","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set"]

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metadata_json:
  {"categories":["Data Processing","DevOps"],"complexity":"medium","use_cases":["migrate Airtable to PostgreSQL","automate database schema creation","transfer structured data between platforms","ETL pipeline construction"],"estimated_setup_minutes":45,"required_services":["Airtable API","PostgreSQL"],"key_features":["schema mapping between Airtable and Postgres","automatic table creation","batch processing for large datasets","preservation of data formats","data relationship maintenance"],"target_audience":["data engineers","devops engineers","database administrators"]}


name: Build a Document-based AI Chatbot with Google Drive, Llama 3, and Qdrant RAG
author_name: Mohsin
author_username: mohsinobsidian
categories: []
created_at: 2025-06-08T07:38:46.273Z
updated_at: 2025-06-08T07:38:46.273Z
url: https://n8n.io/workflows/4773
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Overview
  This template allows users to set up an AI-powered chatbot that retrieves and processes knowledge from Google Drive documents using Retrieval-Augmented Generation (RAG). By leveraging Llama 3 for natural language responses and Qdrant vector storage for document embeddings, this chatbot provides accurate, context-aware answers based on stored files.

  Problem It Solves
  Standard AI chatbots often rely on predefined models with limited real-time knowledge access. This workflow overcomes that limitation by:

  Automatically fetching new documents from Google Drive.

  Embedding knowledge for fast retrieval using Qdrant.

  Generating human-like responses with Llama 3 AI.

  Providing accurate, source-backed answers in conversations.

  Use Cases
  ✔️ Customer Support – Retrieve and summarize FAQs stored in Google Drive. ✔️ Internal Knowledge Base – Automate document-based query responses. ✔️ AI-powered Research Assistant – Search and generate insights from uploaded files. ✔️ Business Automation – Enhance workflows with document-aware chat interactions.

  Setup Instructions
  1️⃣ Google Drive Trigger: Detect & Fetch New Documents
  Watches for new files added to a specific Google Drive folder.

  Retrieves the latest file metadata and passes it into the workflow.

  2️⃣ Processing & Embedding the Document
  The document is downloaded via the Google Drive node.

  Text data is split into smaller, retrievable chunks using Recursive Text Splitter.

  Embeddings are created using Ollama’s Nomic-Embed Model.

  Knowledge is stored in Qdrant Vector Database for fast AI-powered lookup.

  3️⃣ AI Chatbot & Query Handling
  The Chat Trigger node listens for user queries.

  The AI Agent retrieves context-aware answers by searching Qdrant’s vectorized documents.

  The Llama 3 Model generates human-like responses based on stored knowledge.

  Detailed Workflow Explanation
  🔹 Google Drive Trigger
  ✅ Monitors a specific folder for new documents. ✅ Automatically fetches document metadata when a file is uploaded.

  🔹 Qdrant Vector Store
  ✅ Stores embedded document text, making retrieval instant & accurate. ✅ Allows the chatbot to reference stored knowledge dynamically.

  🔹 Recursive Text Splitter
  ✅ Splits long documents into manageable chunks for efficient embedding. ✅ Improves chatbot response accuracy by organizing document data.

  🔹 Llama 3 Chat Model
  ✅ Generates natural, human-like replies using AI. ✅ Uses retrieved document data for context-aware responses.

  Customization Options
  🔹 Adjust polling frequency for document updates. 🔹 Expand knowledge base by adding more storage sources. 🔹 Refine chatbot responses with prompt tuning in Llama 3.

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.embeddingsOllama","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOllama","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.embeddingsOllama","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Data Processing"],"complexity":"medium","use_cases":["build AI support chatbot","integrate Google Drive docs","train metadata RAG models","enable conversational search","create knowledge base bots"],"estimated_setup_minutes":30,"required_services":["Google Drive","Ollama","Qdrant"],"key_features":["document-based conversations","vector store integration","context-aware retrieval","custom LLM responses","file-based knowledge base"],"target_audience":["developers","data analysts"]}


name: Discover & Analyze TikTok Influencers with Bright Data, Claude AI & Email Outreach
author_name: Dvir Sharon
author_username: dvirsharon
categories: []
created_at: 2025-06-08T08:44:40.329Z
updated_at: 2025-06-08T08:44:40.329Z
url: https://n8n.io/workflows/4774
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  🎯 Automated TikTok Influencer Discovery & Analysis

  A complete n8n automation that discovers TikTok influencers using Bright Data, evaluates their fit using Claude AI, and sends personalized outreach emails. Designed for marketing teams and brands that need a scalable, intelligent way to find and connect with relevant creators.

  📋 Overview

  This workflow provides a full-service influencer discovery pipeline: it finds TikTok profiles using search keywords, uses AI to assess alignment with your brand, and initiates contact with qualified influencers. Ideal for influencer marketing, brand partnerships, and campaign planning.

  ✨ Key Features

  🔍 Keyword-Based Discovery**  
    Locate TikTok influencers by specific niche-related keywords.

  📊 Bright Data Integration**  
    Access accurate TikTok profile data from Bright Data’s datasets.

  🤖 AI-Powered Analysis**  
    Claude AI evaluates each profile's fit with your brand based on bio, content, and more.

  📧 Smart Email Notifications**  
    Sends tailored outreach emails to creators deemed highly relevant.

  📈 Data Storage**  
    Google Sheets stores profile details, AI evaluation results, and outreach status.

  🎯 Intelligent Filtering**  
    Processes only influencers who meet your criteria (e.g., 5000+ followers, industry match).

  ⚡ Fast & Reliable**  
    Uses professional scraping with robust error handling.

  🔄 Batch Processing**  
    Supports bulk influencer processing through a single automated flow.

  🎯 What This Workflow Does

  Input

  Search Keywords** – TikTok terms for finding niche creators  
  Business Info** – Brand description and industry  
  Collaboration Criteria** – Follower count minimum, niche alignment

  Processing Steps

  Form Submission  
  TikTok Discovery via Bright Data  
  Data Extraction and Normalization  
  Save to Google Sheets  
  Relevance Scoring via Claude AI  
  Filtering Based on AI Score + Follower Count  
  Personalized Email Outreach

  Output Data Points

  | Field         | Description                        | Example                          |
  |---------------|------------------------------------|----------------------------------|
  | Profile ID    | TikTok profile identifier          | tiktoker123456                   |
  | Username      | TikTok handle                      | @creativecreator                 |
  | URL           | Profile link                       | https://tiktok.com/@creativecreator |
  | Description   | Creator bio                        | "Fashion & lifestyle content..." |
  | Followers     | Total follower count               | 50,000                           |
  | Collaboration | AI assessment of brand fit         | "Highly Relevant"               |
  | Analysis      | 50-word Claude AI relevance summary| "Strong alignment with fashion..."|

  🚀 Setup Instructions

  Prerequisites

  n8n (cloud or self-hosted)  
  Bright Data account with TikTok access  
  Google Sheets + Gmail  
  Anthropic Claude API key  
  10–15 minutes setup time

  Step-by-Step Setup

  Import Workflow via JSON in n8n  
  Configure Bright Data – Add API credentials and dataset ID  
  Google Sheets – Setup credentials and map columns  
  Claude AI – Insert API key and select desired model  
  Gmail – Authenticate Gmail and update mail node settings  
  Update Variables – Replace placeholders with business info  
  Test & Launch – Submit a sample form and verify all outputs

  📖 Usage Guide

  Adding Search Keywords

  Submit the form with search terms, business description, and industry category to trigger the workflow.

  Understanding AI Analysis

  Emails are sent only if:
    Collaboration status = Highly Relevant
    Follower count ≥ 5000
    Industry alignment confirmed
  Claude AI returns a 50-word analysis justifying the match

  Customizing Filters

  Edit the "Find the Collaborator" prompt to adjust:
  Follower thresholds
  Industry relevance
  Additional metrics (e.g., engagement rate)

  Viewing Results

  Google Sheets log includes:
  Influencer metadata
  AI scores and rationale
  Collaboration status
  Email delivery timestamp

  🔧 Customization Options

  Add More Fields:** Engagement rate, contact email, content themes  
  Email Personalization:** Customize message templates or integrate other mail services  
  Enhanced Filtering:** Use engagement rates, region, content frequency

  🚨 Troubleshooting

  | Issue | Fix |
  |-------|-----|
  | Bright Data fails | Recheck API and dataset ID |
  | No influencer data | Adjust keywords or dataset scope |
  | Sheets permission error | Re-authenticate and check sharing |
  | Claude fails | Validate API key and prompt |
  | Emails not sent | Re-auth Gmail or update recipient field |
  | Form not triggering | Reconfirm webhook URL and permissions |

  Advanced Debugging

  Check n8n execution logs  
  Run individual nodes for pinpointing failures  
  Confirm all data formats  
  Handle API rate limits  
  Add error-catch nodes for retries

  📊 Use Cases & Examples

  Brand Discovery:** Fashion, tech, fitness creators  
  Competitor Insights:** Find influencers used by rival brands  
  Campaign Planning:** Build targeted influencer lists  
  Market Research:** Identify creator trends across regions

  ⚙️ Advanced Configuration

  Batch Execution:** Process multiple keywords with delay logic  
  Engagement Metrics:** Scrape and calculate likes-to-follower ratios  
  CRM Integration:** Sync qualified profiles to HubSpot, Salesforce, or Slack

  📈 Performance & Limits

  Processing Time:** 3–5 minutes per keyword  
  Concurrency:** 3–5 simultaneous fetches (depends on plan)  
  Accuracy:** >95% influencer data reliability  
  Success Rate:** 90%+ for outreach and processing

nodes_used:
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metadata_json:
  {"categories":["Marketing"],"complexity":"medium","use_cases":["find TikTok creators","evaluate influencer fit","automate outreach emails"],"estimated_setup_minutes":45,"required_services":["Bright Data","Claude AI","Email Service Provider"],"key_features":["AI-powered content analysis","automated lead generation","personalized email campaigns"],"target_audience":["marketing managers","content creators","brand managers"]}


name: LinkedIn Job Finder Automation using Bright Data API & Google Sheets
author_name: Dvir Sharon
author_username: dvirsharon
categories: []
created_at: 2025-06-08T08:46:42.907Z
updated_at: 2025-06-08T08:46:42.907Z
url: https://n8n.io/workflows/4775
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  💼 LinkedIn Job Finder Automation using Bright Data API & Google Sheets


  A comprehensive n8n automation that searches LinkedIn job postings using Bright Data’s API and automatically organizes results in Google Sheets for efficient job hunting and recruitment workflows.

  📋 Overview
  This workflow provides an automated LinkedIn job search solution that collects job postings based on your search criteria and organizes them in Google Sheets. Perfect for job seekers, recruiters, HR professionals, and talent acquisition teams.

  ✨ Key Features
  🔍 Smart Job Search:** Form-based input for city, job title, country, and job type
  🛍 LinkedIn Integration:** Uses Bright Data’s LinkedIn dataset for accurate job posting data
  📊 Automated Organization:** Populates Google Sheets with structured job data
  📧 Real-time Processing:** Processes job search requests in real-time
  📈 Data Storage:** Stores job details including company info, locations, and apply links
  🔄 Batch Processing:** Handles multiple job postings efficiently
  ⚡ Fast & Reliable:** Built-in error handling for scraping
  🎯 Customizable Filters:** Advanced job filtering based on criteria

  🎯 What This Workflow Does
  Input

  Job Search Criteria:** City, job title, country, and optional job type
  Search Parameters:** Configurable filters and limits
  Output Preferences:** Google Sheets destination

  Processing Steps

  Form Submission
  Data Request to Bright Data API
  Status Monitoring
  Data Extraction
  Data Filtering
  Sheet Update
  Error Handling

  Output Data Points

  Field

  Description

  Example

  Job Title

  Position title from posting

  Senior Software Engineer

  Company Name

  Employer company name

  Tech Solutions Inc.

  Job Detail

  Job summary/description

  Remote position requiring 5+ years…

  Location

  Job location

  San Francisco, CA

  Company URL

  Company profile link

  View Profile

  Apply Link

  Direct application link

  Apply Now

  🚀 Setup Instructions
  Prerequisites

  n8n instance (self-hosted or cloud)
  Google account with Sheets access
  Bright Data account with LinkedIn dataset access

  Steps

  Import the Workflow: Use JSON import in n8n
  Configure Bright Data: Add API credentials and dataset ID
  Configure Google Sheets: Create sheet, set credentials, map columns
  Update Workflow Settings: Replace placeholders with your actual data
  Test & Activate: Submit test form and verify data in Google Sheets

  📖 Usage Guide
  Submitting Job Searches

  Go to your webhook URL and fill in the form with:

  City:** e.g., New York
  Job Title:** e.g., Software Engineer
  Country:** e.g., US
  Job Type:** Optional (Full-Time, Remote, etc.)

  Understanding Results

  Comprehensive job data
  Company info and profile links
  Direct application links
  Location and job descriptions

  Customizing Search Parameters

  Edit the Create Snapshot ID node to change:

  Time range (e.g., “Past month”)
  Result limits
  Company filters

  🔧 Customization Options
  More Data Points:** Add salary, seniority, applicants, etc.
  Custom Form Fields:** Add filters for salary, experience, industry
  Multiple Sheets:** Route results by job type or location

  🚨 Troubleshooting
  Bright Data connection failed:** Check API credentials and dataset access
  No job data extracted:** Verify search parameters and API limits
  Google Sheets permission denied:** Re-authenticate and check sharing
  Form not working:** Check webhook URL and field mappings
  Filter issues:** Review logic and data types
  Execution failed:** Check logs, retry logic, and network status

  📊 Use Cases & Examples
  Job Seeker Dashboard:** Automate job search and track applications
  Recruitment Pipeline:** Source candidates and monitor hiring trends
  Market Research:** Analyze job trends and salary benchmarks
  HR Analytics:** Support workforce planning and competitive insights

  ⚙️ Advanced Configuration
  Batch Processing:** Queue multiple searches with delays
  Search History:** Track and analyze past searches
  Tool Integration:** Connect to CRM, Slack, databases, BI tools

  📈 Performance & Limits
  Processing Time:** 30–60 seconds per search
  Concurrent Requests:** 2–3 (depends on Bright Data plan)
  Data Accuracy:** 95%+
  Success Rate:** 90%+
  Daily Capacity:** 50–200 searches
  Memory:** ~50MB per execution
  API Calls:** 3–4 Bright Data + 1 Google Sheets per search

  🤝 Support & Community
  n8n Community:** community.n8n.io
  Documentation:** docs.n8n.io
  Bright Data Support:** Via your Bright Data dashboard
  GitHub Issues:** Report bugs and request features

  🎯 Ready to Use!
  Your workflow is ready for automated LinkedIn job searching. Customize it to your recruiting or job search needs.

  Webhook URL: https://your-n8n-instance.com/webhook/linkedin-job-finder

  What Gets Extracted:

     *   ✅ Job Title *   ✅ Company Information *   ✅ Location Data *   ✅ Job Details *   ✅ Application Links *   ✅ Processing Timestamps  ### Use Cases:  *   🔍 Job Search Automation *   📊 Recruitment Intelligence *   📝 Market Research *   🎯 HR Analytics   

nodes_used:
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metadata_json:
  {"categories":["DevOps","Data Processing","Communication"],"complexity":"medium","use_cases":["Automated job search","Resume screening","Talent pipeline management"],"estimated_setup_minutes":30,"required_services":["Bright Data","Google Sheets"],"key_features":["LinkedIn API integration","Automated data scraping","Sheet organization","Custom search criteria"],"target_audience":["Recruiters","HR professionals","Job seekers"]}


name: Transform Documents into Engaging LinkedIn Posts with GPT-4.1 and Email Approval
author_name: Yannick
author_username: yjoly
categories: []
created_at: 2025-06-08T09:48:36.844Z
updated_at: 2025-06-08T09:48:36.844Z
url: https://n8n.io/workflows/4777
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  🚀 How it works (Fonctionnement résumé) :

  Ce template permet de transformer un document (PDF, TXT, DocX...) en post LinkedIn engageant, prêt à être publié ou validé par email, le tout avec l’aide d’une IA spécialisée en copywriting LinkedIn. Voici les étapes clés :

  Formulaire de dépôt : L'utilisateur charge un fichier ou colle un texte.
  Détection du type de contenu : Un Switch analyse le type de fichier (PDF, DOCX, TXT, ou texte brut). Attention pour DocX nécessite un compte Make pour transformer le doc (mais cela fonctionne aussi sans docX)
  Extraction du contenu : Selon le format, le bon module d'extraction est utilisé.
  Génération d’un post LinkedIn : L'IA transforme le contenu en post LinkedIn selon une méthodologie de copywriting optimisée.
  Validation par email : Un email est envoyé à l’utilisateur pour approbation avec possibilité d’ajouter une image.
  Publication automatique : Si l'utilisateur valide, le post est publié sur LinkedIn.

  ⚙️ Setup Steps :

  Connecte tes comptes :

     Google Docs OAuth
     LinkedIn OAuth
     OpenAI (via gpt-4.1-mini ou un autre modèle)
     SMTP + IMAP pour l'envoi et la lecture d'emails

  Configure les champs du formulaire dans le nœud Form Trigger selon ton usage.

  Personnalise le prompt IA dans le nœud AI Agent si tu veux adapter le ton ou la méthodologie.

  Vérifie les emails dans le nœud d'envoi (Send Email) et de lecture (Email Trigger (IMAP)), pour que la validation fonctionne.

  Teste le workflow avec différents fichiers pour t'assurer que tous les types sont bien traités (PDF, DOCX, TXT, etc.).

  🧩 Cas d’usage typiques :

  Créer des posts à partir de notes de réunion ou de rapports.
  Valoriser un article ou une publication professionnelle sous forme de contenu LinkedIn.
  Déléguer à l'IA le premier jet de ton contenu réseau.
  Bonus surveille une newsletter de ta messagerie pour proposer un post pertinent sur LinkedIn (vous pouvez supprimer il fonctionne en parallèle)

nodes_used:
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metadata_json:
  {"categories":["Content Creation","Communication","Marketing"],"complexity":"medium","use_cases":["6","6"],"estimated_setup_minutes":10,"required_services":["Google Docs","LinkedIn","Make (Integromat)"],"key_features":["multi-format file ingestion","AI-driven copywriting","email approval routing"],"target_audience":["social media managers","content creators","marketing teams"]}


name: Automatically Sync Google Calendar Events to Google Sheets Tracker
author_name: Shi Varong
author_username: svar-n8n
categories: []
created_at: 2025-06-08T10:07:04.007Z
updated_at: 2025-06-08T10:07:04.007Z
url: https://n8n.io/workflows/4778
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  How it works
  Listens for new or updated events in your chosen Google Calendar.
  Extracts key details like event name, date, time, description, and attendees.
  Adds each event as a new row in your connected Google Sheet.
  Prevents duplicates by checking for existing Event IDs before inserting.

  ✨ Open your spreadsheet to instantly see a clean, structured list of all scheduled events—perfect for reports, planning, or sharing with others who don’t use Google Calendar.



  Set up steps
  Connect your Google Calendar and Google Sheets accounts in n8n.
  Select the calendar you want to monitor and the spreadsheet you want to write to.
  Set up your Google Sheet with appropriate columns (e.g. Event ID, Title, Description, Start Time, End Time, Location).
  Customize your node to match the event fields with spreadsheet columns.
  Enable the workflow and run it once to test.

  ⏱️ Setup Time: ~10–20 minutes depending on familiarity with n8n and Google integrations.

  🔧 No coding required—just drag, drop, and configure nodes.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleCalendar","n8n-nodes-base.if","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Productivity/Automation","Data Processing"],"complexity":"medium","use_cases":["calendar event tracking","data synchronization","report generation","project planning"],"estimated_setup_minutes":10,"required_services":["Google Calendar","Google Sheets"],"key_features":["real-time sync","event deduplication","structured data export","attribute extraction"],"target_audience":["project managers","admin staff","data analysts"]}


name: LinkedIn Job Monitor: Smart Filtering + Google Sheets + Telegram/WhatsApp Alerts
author_name: papcy
author_username: papcy
categories: []
created_at: 2025-06-08T10:51:30.987Z
updated_at: 2025-06-08T10:51:30.987Z
url: https://n8n.io/workflows/4780
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automated LinkedIn Job Monitoring with AI Filtering, Google Sheets & Telegram Alerts

  📋 Description

  Automates LinkedIn job searches across multiple countries and categories, filters results with AI, stores data in Google Sheets, and sends weekly Telegram notifications. Perfect for professionals seeking opportunities in software development, web development, and digital marketing.

  Workflow Process: Weekly scheduler triggers SerpAPI searches → AI processes and filters jobs → Saves to Google Sheets → Sends country-by-country analytics via Telegram/WhatsApp.

  🛠️ Prerequisites

  SerpAPI Account** (free 100 searches/month) - Get API key from serpapi.com
  Telegram Bot Token** - Create via @BotFather
  Google Sheets** - OAuth2 credentials + shareable spreadsheet
  WhatsApp Business Cloud** (optional)

  📋 Setup Instructions

  1. Create Google Spreadsheet
  Set column headers: job_title | company_name | location | salary_raw | salary_numeric | remote_status | description | application_url | date_posted | country | timestamp_added | job_id | source

  2. Replace Placeholders
  YOUR_SERPAPI_KEY_HERE → Your SerpAPI key
  YOUR_GOOGLE_SHEET_ID_HERE → Spreadsheet ID from URL
  YOUR_TELEGRAM_CHAT_ID_HERE → Your Telegram chat ID
  YOUR_PHONE_NUMBER_HERE → WhatsApp number (optional)

  3. Configure Search Parameters
  Modify "Initialize Variables" node:
  job_types: "software development,web development,digital marketing"
  countries: "qatar,uae,saudi arabia"

  4. Set Credentials
  Add SerpAPI HTTP credentials
  Configure Telegram bot credentials
  Set up Google OAuth2 credentials

  Column Requirements: Ensure Google Sheets has exact column names as specified above for proper data mapping.

nodes_used:
  ["n8n-nodes-base.telegramTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.itemLists","n8n-nodes-base.itemLists","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.aggregate","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.whatsApp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Career","Communication","Data Processing"],"complexity":"medium","use_cases":["automated job searches","AI-based job filtering","weekly job alerts","role-specific opportunity tracking"],"estimated_setup_minutes":20,"required_services":["LinkedIn","SerpAPI","Google Sheets","Telegram"],"key_features":["AI-powered job filtering","multi-region job search","scheduled automation","daily email summaries","integrated notifications"],"target_audience":["recruiters","job seekers","HR professionals"]}


name: Get Malaysia Tax ID Number (TIN) for multiple Business Reg Num (SSM) or NRIC
author_name: Alex Halfborg
author_username: halfborg
categories: []
created_at: 2025-06-08T10:51:31.883Z
updated_at: 2025-06-08T10:51:31.883Z
url: https://n8n.io/workflows/4781
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  BACKGROUND
  Malaysia's Inland Revenue (LHDN) provides an API to get the tax id number for a business entity, based on a given Business Registration number (BRN or SSM), or NRIC (MyKad). 

  PROBLEM

  However, the API only allows one search at a time.

  SOLUTION

  This free workflow lets you do a batch search to get TIN for multiple SSM or NRIC. 

  This is useful if you need to prepare your internal DB for e-invoicing

  PRE-REQUISITES

  1) Get your connection client id and client secret from myhasil.gov.my website

  2) Prepare your Google Sheet containing a list of SSM and NRIC you want to get the TIN

  3) Create N8N credential to connect to your google sheet above

  SUPPORT

  Questions? Ask alex at halfborg dot com

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.manualTrigger","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.splitInBatches","n8n-nodes-base.switch","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Data Processing"],"complexity":"medium","use_cases":["Batch retrieve TIN numbers","Validate business registration","Prepare e-invoicing data"],"estimated_setup_minutes":30,"required_services":["Malaysia LHDN API","myhasil.gov.my"],"key_features":["Batch processing capability","Error handling with retries","Data validation"],"target_audience":["accountants","finance teams","data analysts"]}


name: Automated Weekly Google Calendar Summary via Email with AI ✨🗓️📧
author_name: Jez
author_username: jez
categories: []
created_at: 2025-06-08T12:50:39.274Z
updated_at: 2025-06-08T12:50:39.274Z
url: https://n8n.io/workflows/4783
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Workflow: Automated Weekly Google Calendar Summary via Email with AI ✨🗓️📧

  Get a personalized, AI-powered summary of your upcoming week's Google Calendar events delivered straight to your inbox! This workflow automates the entire process, from fetching events to generating an intelligent summary and emailing it to you.

  🌟 Overview

  This n8n workflow connects to your Google Calendar, retrieves events for the upcoming week (Monday to Sunday, based on the day the workflow runs), uses Google Gemini AI to create a well-structured and insightful summary, and then emails this summary to you. It's designed to help you start your week organized and aware of your commitments.

  Key Features:

  Automated Weekly Summary:** Runs on a schedule (default: weekly) to keep you updated.
  AI-Powered Insights:** Leverages Google Gemini to not just list events, but to identify important ones and offer a brief weekly outlook.
  Personalized Content:** Uses your specified timezone, locale, name, and city for accurate and relevant information.
  Clear Formatting:** Events are grouped by day and displayed chronologically with start and end times. Important events are highlighted.
  Email Delivery:** Receive your schedule directly in your inbox in a clean HTML format.
  Customizable:** Easily adapt to your specific calendar, AI preferences, and email settings.

  ⚙️ How It Works: Step-by-Step

  The workflow consists of the following nodes, working in sequence:

  weekly_schedule (Schedule Trigger):
      What it does: Initiates the workflow.
      Default: Triggers once a week at 12:00 PM. You can adjust this to your preference (e.g., Sunday evening or Monday morning).

  locale (Set Node):
      What it does: This is a crucial node for you to configure! It sets user-specific parameters like your preferred language/region (users-locale), timezone (users-timezone), your name (users-name), and your home city (users-home-city). These are used throughout the workflow for correct date/time formatting and personalizing the AI prompt.

  date-time (Set Node):
      What it does: Dynamically generates various date and time strings based on the current execution time and the locale settings. This is used to define the precise 7-day window (from the current day to 7 days ahead, ending at midnight) for fetching calendar events.

  get_next_weeks_events (Google Calendar Node):
      What it does: Connects to your specified Google Calendar and fetches all events within the 7-day window calculated by the date-time node.
      Requires: Google Calendar API credentials and the ID of the calendar you want to use.

  simplify_evens_json (Code Node):
      What it does: Runs a small JavaScript snippet to clean up the raw event data from Google Calendar. It removes several fields that aren't needed for the summary (like htmlLink, etag, iCalUID), making the data more concise for the AI.

  aggregate_events (Aggregate Node):
      What it does: Takes all the individual (and now simplified) event items and groups them into a single JSON array called eventdata. This is the format the AI agent expects for processing.

  Google Gemini (LM Chat Google Gemini Node):
      What it does: This node is the connection point to the Google Gemini language model.
      Requires: Google Gemini (or PaLM) API credentials.

  event_summary_agent (Agent Node):
      What it does: This is where the magic happens! It uses the Google Gemini model and a detailed system prompt to generate the weekly schedule summary.
      The Prompt Instructs the AI to:
          Start with a friendly greeting.
          Group events by day (Monday to Sunday) for the upcoming week, using the user's timezone and locale.
          Format event times clearly (e.g., 09:30 AM - 10:30 AM: Event Summary).
          Identify and prefix "IMPORTANT:" to events with keywords like "urgent," "deadline," "meeting," etc., in their summary or description.
          Conclude with a 1-2 sentence helpful insight about the week's schedule.
          Process the input eventdata (the JSON array of calendar events).

  Markdown (Markdown to HTML Node):
      What it does: Converts the text output from the event_summary_agent (which is generated in Markdown format for easy structure) into HTML. This ensures the email body is well-formatted with proper line breaks, lists, and emphasis.

  send_email (Email Send Node):
      What it does: Sends the final HTML summary to your specified email address.
      Requires: SMTP (email sending) credentials and your desired "From" and "To" email addresses.

  🚀 Getting Started: Setup Instructions

  Follow these steps to get the workflow up and running:

  Import the Workflow:
      Download the workflow JSON file.
      In your n8n instance, go to "Workflows" and click the "Import from File" button. Select the downloaded JSON file.

  Configure Credentials:
      You'll need to set up credentials for three services. In n8n, go to "Credentials" on the left sidebar and click "Add credential."
      Google Calendar API:
          Search for "Google Calendar" and create new credentials using OAuth2. Follow the authentication flow.
          Once created, select these credentials in the get_next_weeks_events node.
      Google Gemini (PaLM) API:
          Search for "Google Gemini" or "Google PaLM" and create new credentials. You'll typically need an API key from Google AI Studio or Google Cloud.
          Once created, select these credentials in the Google Gemini node.
      SMTP / Email:
          Search for your email provider (e.g., "SMTP," "Gmail," "Outlook") and create credentials. This usually involves providing your email server details, username, and password/app password.
          Once created, select these credentials in the send_email node.

  ‼️ IMPORTANT: Customize User Settings in the locale Node:
      Open the locale node.
      Update the following values in the "Assignments" section:
          users-locale: Set your locale string (e.g., "en-AU" for English/Australia, "en-US" for English/United States, "de-DE" for German/Germany). This affects how dates, times, and numbers are formatted.
          users-timezone: Set your timezone string (e.g., "Australia/Sydney", "America/New_York", "Europe/London"). This is critical for ensuring event times are displayed correctly for your location.
          users-name: Enter your name (e.g., "Bob"). This is used to personalize the email greeting.
          users-home-city: Enter your home city (e.g., "Sydney"). This can be used for additional context by the AI.

  Configure the get_next_weeks_events (Google Calendar) Node:
      Open the node.
      In the "Calendar" parameter, you need to specify which calendar to fetch events from.
          The default might be a placeholder like c_4d9c2d4e139327143ee4a5bc4db531ffe074e98d21d1c28662b4a4d4da898866@group.calendar.google.com.
          Change this to your primary calendar (often your email address) or the specific Calendar ID you want to use. You can find Calendar IDs in your Google Calendar settings.

  Configure the send_email Node:
      Open the node.
      Set the fromEmail parameter to the email address you want the summary to be sent from.
      Set the toEmail parameter to the email address(es) where you want to receive the summary.
      You can also customize the subject line if desired.

  (Optional) Customize the AI Prompt in event_summary_agent:
      If you want to change how the AI summarizes events (e.g., different keywords for important events, a different tone, or specific formatting tweaks), you can edit the "System Message" within the event_summary_agent node's parameters.

  (Optional) Adjust the Schedule in weekly_schedule:
      Open the weekly_schedule node.
      Modify the "Rule" to change when and how often the workflow runs (e.g., a specific day of the week, a different time).

  Activate the Workflow:
      Once everything is configured, toggle the "Active" switch in the top right corner of the workflow editor to ON.

  📬 What You Get

  You'll receive an email (based on your schedule) with a subject like "Next Week Calendar Summary : [Start Date] - [End Date]". The email body will contain:

  A friendly greeting.
  Your schedule for the upcoming week (Monday to Sunday), with events listed chronologically under each day.
  Event times displayed in your local timezone (e.g., 09:30 AM - 10:30 AM: Team Meeting).
  Priority events clearly marked (e.g., IMPORTANT: 02:00 PM - 03:00 PM: Project Deadline Review).
  A brief, insightful observation about your week's schedule.

  🛠️ Troubleshooting & Notes

  Timezone is Key:** Ensure your users-timezone in the locale node is correct. This is the most common source of incorrect event times.
  Google API Permissions:** When setting up Google Calendar and Gemini credentials, make sure you grant the necessary permissions.
  AI Output Varies:** The AI-generated summary can vary slightly each time. The prompt is designed to guide it, but LLMs have inherent creativity.
  Calendar Event Details:** The quality of the summary (especially for identifying important events) depends on how detailed your calendar event titles and descriptions are. Including keywords like "meeting," "urgent," "prepare for," etc., in your events helps the AI.

  💬 Feedback & Contributions

  Feel free to modify and enhance this workflow! If you have suggestions, improvements, or run into issues, please share them in the n8n community.

  Happy scheduling!

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name: Track Technology Stacks & Find Decision Makers with BuiltWith to Google Sheets
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:04:50.134Z
updated_at: 2025-06-08T14:04:50.134Z
url: https://n8n.io/workflows/4784
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automated system to track and analyze technology stacks used by target companies, helping identify decision-makers and technology trends.

  🚀 What It Does

  Tracks technology stack of target companies
  Identifies key decision-makers (CTOs, Tech Leads)
  Monitors technology changes and updates
  Provides competitive intelligence
  Generates actionable insights

  🎯 Perfect For

  B2B SaaS companies
  Technology vendors
  Sales and business development teams
  Competitive intelligence analysts
  Market researchers

  ⚙️ Key Benefits

  ✅ Identify potential customers  
  ✅ Stay ahead of technology trends  
  ✅ Target decision-makers effectively  
  ✅ Monitor competitor technology stacks  
  ✅ Data-driven sales strategies  

  🔧 What You Need

  BuiltWith API key
  n8n instance
  CRM integration (optional)
  Email/Slack for alerts

  📊 Data Tracked

  Company technologies
  Hosting providers
  Frameworks and libraries
  Analytics tools
  Marketing technologies

  🛠️ Setup & Support

  Quick Setup

  Deploy in 20 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Gain a competitive edge by understanding the technology landscape of your target market.

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name: Export & Organize Technology Stack Data From BuiltWith to Google Sheets
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:05:16.483Z
updated_at: 2025-06-08T14:05:16.483Z
url: https://n8n.io/workflows/4785
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automated pipeline that exports technology stack data from BuiltWith to Google Sheets for analysis, reporting, and team collaboration.

  🚀 What It Does

  Extracts technology stack data
  Organizes data in Google Sheets
  Updates automatically on schedule
  Supports multiple company tracking
  Enables easy data sharing

  🎯 Perfect For

  Sales teams
  Market researchers
  Business analysts
  Competitive intelligence
  Technology consultants

  ⚙️ Key Benefits

  ✅ Centralized technology database  
  ✅ Easy data analysis  
  ✅ Team collaboration  
  ✅ Historical tracking  
  ✅ Custom reporting  

  🔧 What You Need

  BuiltWith API access
  Google account
  n8n instance
  Google Sheets setup

  📊 Data Exported

  Company information
  Web technologies
  Hosting details
  Analytics tools
  Marketing technologies
  Contact information

  🛠️ Setup & Support

  Quick Setup

  Start exporting in 15 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Transform raw technology data into actionable business intelligence with automated exports.

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name: Automate Sales Pipeline: BuiltWith Technology Data to Trello Lead Cards with Google Sheets
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:05:42.263Z
updated_at: 2025-06-08T14:05:42.263Z
url: https://n8n.io/workflows/4786
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Automated workflow that transforms BuiltWith technology data into actionable sales leads in Trello, creating a visual sales pipeline.

  🚀 What It Does

  Converts tech stack data into Trello cards
  Organizes leads by technology stack
  Tracks sales pipeline stages
  Enables team collaboration
  Updates automatically

  🎯 Perfect For

  Sales teams
  Business development
  Account executives
  Tech startups
  Digital agencies

  ⚙️ Key Benefits

  ✅ Visual sales pipeline  
  ✅ Easy lead qualification  
  ✅ Team collaboration  
  ✅ Technology-based filtering  
  ✅ Automated data entry  

  🔧 What You Need

  BuiltWith API access
  Trello account
  n8n instance
  Google account (for authentication)

  📊 Data Mapped to Trello

  Company details
  Technology stack
  Contact information
  Website metrics
  Custom labels

  🛠️ Setup & Support

  Quick Setup

  Start in 20 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Turn technology intelligence into sales opportunities with automated lead management.

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name: Track Technology Changes with BuiltWith and Log to Google Sheets
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:06:13.019Z
updated_at: 2025-06-08T14:06:13.019Z
url: https://n8n.io/workflows/4787
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automated monitoring system that sends instant alerts when target companies make technology changes, delivered directly to your inbox or Slack.

  🚀 What It Does

  Monitors technology stack changes
  Sends real-time email alerts
  Posts updates to Slack
  Tracks historical changes
  Filters by technology type

  🎯 Perfect For

  Sales teams
  IT departments
  Competitive intelligence
  Technology vendors
  Market researchers

  ⚙️ Key Benefits

  ✅ Instant technology change alerts  
  ✅ Multiple notification channels  
  ✅ Historical tracking  
  ✅ Customizable filters  
  ✅ Team collaboration  

  🔧 What You Need

  BuiltWith API access
  Email service (SMTP/SendGrid)
  Slack workspace (optional)
  n8n instance

  📊 Alerts Include

  Company name
  Technology changes
  Timestamp
  Impact assessment
  Direct links

  🛠️ Setup & Support

  Quick Setup

  Get alerts in 15 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Stay informed about technology changes that matter to your business with automated monitoring alerts and notifications.

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metadata_json:
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name: Automated Weekly Tech Stack Reports with BuiltWith, GPT-4o & Gmail
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:06:39.725Z
updated_at: 2025-06-08T14:06:39.725Z
url: https://n8n.io/workflows/4788
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automated weekly report that summarizes technology stack changes, trends, and insights from your tracked companies.

  🚀 What It Does

  Compiles weekly technology updates
  Highlights significant changes
  Identifies emerging trends
  Provides actionable insights
  Delivers scheduled reports

  🎯 Perfect For

  CTOs and technical leaders
  Sales and marketing teams
  Business intelligence
  Technology consultants
  Market researchers

  ⚙️ Key Benefits

  ✅ Weekly digest of changes  
  ✅ Trend analysis  
  ✅ Competitive intelligence  
  ✅ Time-saving automation  
  ✅ Data-driven decisions  

  🔧 What You Need

  BuiltWith API access
  n8n instance
  Email service (for delivery)
  Google Sheets (for data storage)

  📊 Report Includes

  New technology adoptions
  Technology removals
  Industry trends
  Competitive analysis
  Custom metrics

  🛠️ Setup & Support

  Quick Setup

  Get your first report in 15 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Stay ahead of technology trends with a comprehensive weekly digest of your industry's technology landscape.

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name: CrunchBase Competitor Intelligence Tracker
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:07:13.023Z
updated_at: 2025-06-08T14:07:13.023Z
url: https://n8n.io/workflows/4789
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Automated system for monitoring and analyzing competitor activities, funding rounds, and market movements using CrunchBase data.

  🚀 What It Does

  Tracks competitor funding rounds
  Monitors leadership changes
  Analyzes investment patterns
  Identifies new market entries
  Tracks product launches

  🎯 Perfect For

  Startup founders
  Business strategists
  Market analysts
  Investment professionals
  Corporate development

  ⚙️ Key Benefits

  ✅ Competitive intelligence  
  ✅ Early warning system  
  ✅ Market trend analysis  
  ✅ Strategic insights  
  ✅ Time-saving automation  

  🔧 What You Need

  CrunchBase API access
  n8n instance
  Google Sheets (for data storage)
  Notification preferences

  📊 Tracking Metrics

  Funding amounts and rounds
  Investor networks
  Hiring trends
  Market expansion
  Product updates

  🛠️ Setup & Support

  Quick Setup

  Start tracking in 20 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Gain a competitive edge with automated tracking and analysis of your competitors' activities and strategies.

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name: Personalized CrunchBase Lead Outreach with AI-Generated Summaries and Gmail
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:07:42.423Z
updated_at: 2025-06-08T14:07:42.423Z
url: https://n8n.io/workflows/4790
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Automated outreach system that identifies and contacts potential leads from CrunchBase with personalized, timely messages.

  🚀 What It Does

  Identifies target companies and contacts
  Personalizes email content
  Schedules follow-ups
  Tracks responses
  Integrates with email providers

  🎯 Perfect For

  Sales development reps
  Business development teams
  Startup founders
  Investment professionals
  Partnership managers

  ⚙️ Key Benefits

  ✅ Automated lead generation  
  ✅ Personalized outreach at scale  
  ✅ Follow-up automation  
  ✅ Response tracking  
  ✅ Time-saving workflow  

  🔧 What You Need

  CrunchBase API access
  Email service (e.g., Gmail, SendGrid)
  n8n instance
  CRM (optional)

  📊 Features

  Contact information extraction
  Email template personalization
  Send time optimization
  Open/click tracking
  Response handling

  🛠️ Setup & Support

  Quick Setup

  Start sending in 30 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Transform your outbound sales process with automated, personalized outreach to high-quality leads from CrunchBase.

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name: Track Investor Data from Crunchbase to Google Sheets for Market Analysis
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:08:56.505Z
updated_at: 2025-06-08T14:08:56.505Z
url: https://n8n.io/workflows/4791
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automated pipeline to collect and analyze investor data from Crunchbase, tracking investment patterns, funding history, and portfolio companies for market analysis and lead generation.

  🚀 What It Does

  Investor Profiling**: Collects comprehensive data on investors and VC firms
  Investment Pattern Analysis**: Tracks funding history and investment preferences
  Portfolio Monitoring**: Keeps tabs on investor portfolios and new investments
  Data Enrichment**: Enhances raw data with additional context and metrics

  🎯 Perfect For

  Startup founders seeking investors
  Market research analysts
  Investment professionals
  Business development teams
  Competitive intelligence

  ⚙️ Key Benefits

  ✅ Comprehensive investor profiles  
  ✅ Real-time investment tracking  
  ✅ Market trend analysis  
  ✅ Data-driven investment decisions  
  ✅ Time-saving automation  

  🔧 What You Need

  Crunchbase API access
  n8n instance
  Storage solution (database or spreadsheet)

  📊 Data Points Collected

  Investor/Firm details
  Investment history
  Portfolio companies
  Funding rounds participated in
  Investment focus areas
  Contact information (when available)

  🛠️ Setup & Support

  Quick Setup

  Deploy in 30 minutes with our step-by-step configuration guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Transform your investor research with automated data collection and analysis. Spend less time gathering data and more time making strategic decisions.

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name: Real-Time Startup Intelligence: Crunchbase Monitoring with AI Summaries & Email Alerts
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:09:23.667Z
updated_at: 2025-06-08T14:09:23.667Z
url: https://n8n.io/workflows/4792
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automated monitoring system that tracks startup activities, funding events, and company updates in real-time, providing valuable market intelligence.

  🚀 What It Does

  Real-time monitoring of startup activities
  Funding alerts and updates
  Competitor tracking
  Industry trend analysis
  Customizable watchlists

  🎯 Perfect For

  Venture capitalists
  Startup founders
  Business development teams
  Market researchers
  Investment analysts

  ⚙️ Key Benefits

  ✅ Stay ahead of market movements  
  ✅ Never miss important funding rounds  
  ✅ Track competitor activities  
  ✅ Identify emerging trends  
  ✅ Save hours of manual research  

  🔧 What You Need

  Crunchbase API access
  n8n instance
  Notification preferences (email/Slack/Teams)

  📊 Data Points Tracked

  New funding rounds
  Company updates
  Leadership changes
  Product launches
  Market expansions

  🛠️ Setup & Support

  Quick Setup

  Deploy in 20 minutes with our step-by-step configuration guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Stay informed about the startup ecosystem with automated monitoring and alerts. Make data-driven decisions with timely, relevant information.

nodes_used:
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metadata_json:
  {"categories":["AI/ML","Data Processing","Marketing"],"complexity":"medium","use_cases":["startup monitoring","funding alerts","competitor tracking"],"estimated_setup_minutes":15,"required_services":["Crunchbase","Email Service"],"key_features":["real-time data monitoring","AI-generated summaries","automated alerts"],"target_audience":["venture capitalists","startup founders","business development teams"]}


name: Upwork Job Aggregator with OpenAI Summaries & Multi-channel Notifications
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:10:05.159Z
updated_at: 2025-06-08T14:10:05.159Z
url: https://n8n.io/workflows/4793
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automated system that aggregates job postings from Upwork based on your criteria and delivers personalized notifications, helping you never miss relevant opportunities.

  🚀 What It Does

  Custom job search based on keywords, skills, and categories
  Real-time job posting monitoring
  Smart filtering and prioritization
  Multi-channel notifications (Email/Slack/Teams)
  Duplicate detection

  🎯 Perfect For

  Freelancers seeking new opportunities
  Agencies looking for projects
  Recruiters sourcing talent
  Business owners finding contractors
  Digital nomads

  ⚙️ Key Benefits

  ✅ Save hours of manual searching  
  ✅ Get notified about relevant jobs first  
  ✅ Never miss perfect opportunities  
  ✅ Customizable search criteria  
  ✅ Time-zone friendly notifications  

  🔧 What You Need

  Upwork account
  n8n instance
  Preferred notification channels setup

  📊 Features

  Custom keyword alerts
  Budget range filtering
  Client history analysis
  Job type filtering (hourly/fixed)
  Experience level filtering

  🛠️ Setup & Support

  Quick Setup

  Be up and running in 15 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Transform your freelance career with automated job hunting. Spend less time searching and more time winning projects.

nodes_used:
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metadata_json:
  {"categories":["Freelancing","Recruitment","Job Search"],"complexity":"medium","use_cases":["automate job searching","filter freelance projects","receive job alerts","unify job sources","notify new leads"],"estimated_setup_minutes":15,"required_services":["Upwork","Slack","Microsoft Teams","Email Providers","Google Sheets"],"key_features":["keyword based filtering","AI generated summaries","channel notifications","duplicate removal","scheduled execution"],"target_audience":["freelancers","recruiters","agencies"]}


name: Upwork Lead Generation: Extract Client Emails with LinkedIn Scraping and AI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:10:26.119Z
updated_at: 2025-06-08T14:10:26.119Z
url: https://n8n.io/workflows/4794
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  Automated solution to extract and organize contact information from Upwork job postings, enabling direct outreach to potential clients who post jobs matching your expertise.

  🚀 What It Does

  Scrapes job postings for contact information
  Extracts email addresses and social profiles
  Organizes leads in a structured format
  Enables direct outreach campaigns
  Tracks response rates

  🎯 Perfect For

  Freelancers looking to expand their client base
  Agencies targeting specific industries
  Sales professionals in the gig economy
  Recruiters sourcing clients
  Digital marketing agencies

  ⚙️ Key Benefits

  ✅ Access to hidden contact information  
  ✅ Expand your client base  
  ✅ Beat the competition to opportunities  
  ✅ Targeted outreach campaigns  
  ✅ Higher response rates  

  🔧 What You Need

  Upwork account
  n8n instance
  Email service (for outreach)
  CRM (optional)

  📊 Features

  Email pattern detection
  Social media profile extraction
  Company website discovery
  Lead scoring system
  Outreach tracking

  🛠️ Setup & Support

  Quick Setup

  Start collecting leads in 20 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Take control of your freelance career with direct access to potential clients. Transform how you find and secure projects on Upwork.

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name: Upwork Job Listings Auto-Export to Google Sheets with Apify
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:10:55.857Z
updated_at: 2025-06-08T14:10:55.857Z
url: https://n8n.io/workflows/4795
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Automated pipeline that extracts job listings from Upwork and exports them to Google Sheets for better organization, analysis, and team collaboration.

  🚀 What It Does

  Fetches job postings based on saved searches
  Extracts key job details (title, budget, description)
  Organizes data in Google Sheets
  Updates in real-time
  Supports multiple search criteria

  🎯 Perfect For

  Freelancers tracking opportunities
  Teams managing multiple projects
  Agencies monitoring client needs
  Market researchers
  Business analysts

  ⚙️ Key Benefits

  ✅ Centralized job board  
  ✅ Easy sharing with team members  
  ✅ Advanced filtering and sorting  
  ✅ Historical data tracking  
  ✅ Customizable data points  

  🔧 What You Need

  Upwork account
  Google account
  n8n instance
  Google Sheets setup

  📊 Data Exported

  Job title and description
  Budget and hourly rate
  Client information
  Posted date
  Required skills
  Job URL

  🛠️ Setup & Support

  Quick Setup

  Get started in 15 minutes with our step-by-step guide

  📺 Watch Tutorial

  💼 Get Expert Support

  📧 Direct Help



  Streamline your job search and opportunity tracking with automated data collection and organization.

nodes_used:
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metadata_json:
  {"categories":["Freelance Services","Data Processing","Business Automation"],"complexity":"simple","use_cases":["extract upwork jobs","export to google sheets","track job opportunities"],"estimated_setup_minutes":15,"required_services":["upwork","google sheets","apify"],"key_features":["job discovery","data extraction","automatic sheet updates","search criteria management"],"target_audience":["freelancers","recruiters","marketing teams"]}


name: Track US Fintech & Healthtech Funding Rounds: Crunchbase to Google Sheets
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-06-08T14:12:37.205Z
updated_at: 2025-06-08T14:12:37.205Z
url: https://n8n.io/workflows/4796
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Track US Fintech & Healthtech Funding Rounds: Crunchbase to Google Sheets

  🌍 Overview

  This workflow fetches the latest funding rounds from Crunchbase (filtered by industry + location), formats the results, and saves them neatly into Google Sheets every day.

  You end up with a live deal flow tracker that updates itself!

  🟢 Section 1: Schedule & Data Fetch

  🔗 Nodes:
  1️⃣ Daily Check for New Funding Rounds (Schedule Trigger)
  ⏰ Runs automatically every morning at 8 AM.

  Why it’s useful: You don’t need to run it manually.

  2️⃣ Fetch Crunchbase Funding Rounds (HTTP Request)
  🌐 Pulls funding rounds from Crunchbase’s API.

  Filters:

    📍 Location → United States
    🏭 Industry → Fintech, Healthtech
    ⏳ Sorted → newest first
    📄 Limit → 25 per run

  💡 Beginner Benefit:
  ✅ No coding required to hit Crunchbase API
  ✅ Automated — always fetches fresh funding data

  🔵 Section 2: Extract & Format

  🔗 Nodes:
  3️⃣ Extract & Format Funding Data (Code)
  📑 Converts Crunchbase API JSON into clean, readable rows with:

  🏢 Company Name
  🏭 Industry
  💵 Money Raised (USD)
  📅 Announced Date
  🏷️ Funding Round Type
  👥 Investors
  🔗 Crunchbase URL

  💡 Beginner Benefit:
  ✅ No messy JSON → clean structured output
  ✅ Auto-creates a link to each funding round

  🟣 Section 3: Save to Sheets

  🔗 Nodes:
  4️⃣ Save to Google Sheets
  📊 Appends the formatted funding round data into your Google Sheet.

  Columns: Company, Industry, Investors, Amount, Date, URL, etc.

  💡 Beginner Benefit:
  ✅ Data goes directly into Google Sheets → no copy-paste
  ✅ You can filter, chart, or connect Sheets to dashboards

  📊 Final Overview

  | Section   | What Happens          | Why It’s Useful                                 |
  | --------- | --------------------- | ----------------------------------------------- |
  | 🟢 Fetch  | Scheduler + API fetch | Always pulls new Crunchbase deals automatically |
  | 🔵 Format | Extract + clean JSON  | Turns raw API data into readable rows           |
  | 🟣 Save   | Google Sheets         | Creates your own funding tracker sheet          |

  🚀 Why This Workflow is a Game-Changer

  ⏱️ Zero manual work → Wake up to fresh funding data daily
  📊 Deal flow in Sheets → Perfect for VCs, founders, analysts
  🔍 Customizable filters → Change location, industry, or # of results
  🔗 Action-ready → Use Sheets to track trends, outreach investors, or monitor competitors

  ✨ With this workflow, you’ve basically built your own Crunchbase alerts dashboard — no coding required!

nodes_used:
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metadata_json:
  {"categories":["Data Processing","Finance"],"complexity":"medium","use_cases":["monitor deal flow","track investment activity","update spreadsheets with data","schedule daily reports"],"estimated_setup_minutes":15,"required_services":["Crunchbase","Google Sheets"],"key_features":["scheduled automated data fetching","industry and location filtering","data formatting and transformation","regular automatic overwrites"],"target_audience":["investment analysts","financial operators"]}


name: Track CVE Vulnerability Details & History with NVD API and Google Sheets
author_name: Niranjan G
author_username: niranjan
categories: []
created_at: 2025-06-08T15:14:27.731Z
updated_at: 2025-06-08T15:14:27.731Z
url: https://n8n.io/workflows/4797
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Who is this for?

  NVD (National Vulnerability Database) data is essential for security analysts, vulnerability managers, and DevSecOps professionals who need to perform both CVE lookups and monitor historical change logs. This workflow helps streamline those efforts by providing structured outputs for audit, triage, or compliance tracking purposes.

  📝 Note: While this example uses Google Sheets as the destination, you can easily modify the final destination node (e.g., send to Slack, email, database, etc.) based on your specific automation needs.?

  What problem is this solving?

  Security teams often manually look up CVE data and track changes across multiple tools. This process is inefficient and error-prone. This workflow automates the CVE lookup and historical change tracking by logging enriched vulnerability data into Google Sheets in real-time.

  What this workflow does

  This workflow is designed for CVE API lookup and change history tracking. In many vulnerability automation pipelines, it is essential to determine not only the metadata of a CVE but also how it has evolved over time. Based on the operational need—whether it's enrichment, risk scoring, or remediation validation—this workflow becomes particularly handy in surfacing both current and historical CVE data. This template performs the following actions:

  Accepts incoming webhook requests containing a CVE ID
  Queries the NVD CVE Lookup API to fetch vulnerability metadata
  Queries the NVD CVE History API to retrieve all historical changes
  Flattens both datasets into a sheet-compatible structure
  Appends vulnerability metadata to one sheet and change history to another within the same Google Spreadsheet

  Setup

  🔑 Request an NVD API Key

  To request an NVD API Key, please provide your organization name, a valid email address, and indicate your organization type at NVD API Key Request. You must scroll to the end of the Terms of Use Agreement and check "I agree to the Terms of Use" to obtain an API Key. After submission, you will receive a single-use hyperlink via email to activate and view your API Key. If not activated within seven days, a new request must be submitted.

  📊 API Rate Limits

  Without an API key, you're limited to 5 requests per 30-second window. With an API key, you’re allowed up to 50 requests in the same period. To prevent request throttling, it's recommended to introduce slight delays between consecutive API calls in production setups.

  Clone or import this workflow into your n8n instance.
  Set up the following credentials:
     Google Sheets OAuth2
     NVD API Key (via HTTP Header Auth)
  The workflow logs data to a Google Sheet titled NVD Database, with Sheet 1 named CVE Lookup and Sheet 2 named CVE History.
  Trigger each workflow using the respective webhook URL, appending ?cveId=CVE-XXXX-XXXX as a query parameter.

  🔍 Example Webhook Request (CVE Change History)

  You can test this workflow with the following example:

  GET https://your-domain.com/webhook/cve-history?cveId=CVE-2023-34362

  How to customize this workflow

  Use the Edit Fields node (optional) to centralize configuration like sheet name or query input
  Extend the CVE flattening logic to include more nested metadata if needed
  Integrate notification systems (e.g., Slack or email) by branching from the processing nodes
  Modify webhook paths for better endpoint organization

  🔐 Production Security Tips

  Use HTTP Header Auth on the webhook for secure access

  &gt; ⚠️ This template uses webhooks and NVD API access with authentication headers.

  This template uses two flows:

  Webhook 1:** NVD CVE Lookup — Lookup CVE vulnerability metadata from NVD and sync to Google Sheet
  Webhook 2:** NVD CVE Change History — Track change history for CVEs via NVD and log each update

  Each flow:

  Hits NVD’s respective endpoint
  Uses custom JS Code node to flatten the nested JSON
  Syncs data to dedicated Google Sheet tabs
  🧩 4 nodes: Webhook → API Call → Parse → Sheet Sync

  Make sure both flows are activated and webhooks exposed for external access. Based on your needs, ensure you have a secure setup—whether hosted internally or in a cloud environment—when running n8n in production.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.webhook","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4300 characters]

metadata_json:
  {"categories":["DevOps","Security"],"complexity":"medium","use_cases":["lookup Cve details","track vulnerability history","monitor nvd changes","audit security logs","compliance reporting"],"estimated_setup_minutes":12,"required_services":["NVD","Google Sheets"],"key_features":["CVE lookup automation","Vulnerability history tracking","Audit trail documentation","Historical change monitoring","Compliance data accumulation"],"target_audience":["security analysts","vulnerability managers","devsecops professionals"]}


name: Create Character-Consistent Images with FLUX Kontext & Post to Social via Upload Post
author_name: Eduard
author_username: eduard
categories: []
created_at: 2025-06-08T15:34:39.639Z
updated_at: 2025-06-08T15:34:39.639Z
url: https://n8n.io/workflows/4798
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Create, iterate, and share! Transform a single image through multiple scenes while maintaining consistency.

  ✨ What this workflow does

  This template showcases FLUX.1 Kontext - Black Forest Labs' in-context image generation model that excels at maintaining character features across multiple transformations. Combined with the Upload Post community node for effortless multi-platform social media posting, you can create and share compelling visual stories instantly.

  The workflow demonstrates FLUX Kontext's core strength: character consistency across multiple image generations. Starting with a single input image, it:
  🖼️ Loads an initial character image (example: a cute animal mascot)
  📝 Defines multiple scene transformation prompts 
  🔄 Iteratively generates new scenes while preserving exact character features
  🎯 Maintains visual consistency by reusing binary data from previous generations
  📱 Auto-posts the complete transformation series to multiple social platforms simultaneously

  🚀 Key Features: The Consistency Advantage

  Character Preservation**: FLUX Kontext's signature feature - maintains character features and style across transformations (requires specific prompting techniques)
  Iterative Context Building**: Each generation uses the previous image as context, creating visual continuity
  Binary Data Reuse**: Smart workflow design that feeds output from one generation as input to the next
  Multi-Scene Storytelling**: Transform your character across different environments while keeping them recognizable
  One-Click Multi-Platform Posting*: Upload Post eliminates the tedious process of posting to each platform individually

  📱 Why use Upload Post?

  Posting the same content to TikTok, Instagram, LinkedIn, YouTube, Facebook, X (Twitter), and Threads individually is time-consuming and error-prone. The Upload Post service* simplifies this process:

  ✅ Connect once, post everywhere: Link all your social media accounts to Upload Post  
  ✅ Single API call: Post to multiple platforms with one simple node  
  ✅ No more platform juggling: Skip the endless switching between apps and dashboards  
  ✅ Consistent timing: All platforms get your content simultaneously  
  ✅ Trusted by 3,751+ users: Proven solution for content creators and marketers

  Instead of spending 30+ minutes manually posting to each platform, Upload Post does it all in seconds with a single n8n node!

  🛠️ Prerequisites

  Required Accounts:
  Black Forest Labs API: Create account at dashboard.bfl.ai
     Get your API key for FLUX Kontext Pro access
     
  Upload Post Account: Sign up at upload-post.com*
     Connect your social media profiles (TikTok, Instagram, LinkedIn, YouTube, Facebook, X/Twitter, Threads)
     Get API credentials for automated posting
     Free tier available: 10 uploads/month

  💡 Perfect For:

  Character Designers** maintaining brand character integrity across scenes
  Social Media Managers** creating engaging visual story series without manual posting
  Brand Marketers** ensuring character consistency across campaigns
  Storytellers** building visual narratives with consistent protagonists
  Agencies** managing multiple client accounts efficiently

  🔧 Customization Options:

  Modify transformation prompts** to create your own character journey
  Adjust iteration steps**
  Change initial character image**
  Configure social platform targeting** (choose which platforms to post to)
  Customize post content** and formatting
  Experiment with different consistency scenarios**

  \ Affiliate link*

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.github","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.executeWorkflow","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-upload-post.uploadPost","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5272 characters]

metadata_json:
  {"categories":["AI/ML"],"complexity":"medium","use_cases":["Generate character-consistent variations","Maintain visual identity across scenes","Automate social media image sharing","Iterate on creative concepts","Create magical realism composite images"],"estimated_setup_minutes":45,"required_services":["Figma","N8N","Upload Post","Secrets (Environment Variables)"],"key_features":["In-context image generation","Multi-platform social media posting","Visual consistency maintenance","Workflow-based iteration","Serial image transformation"],"target_audience":["content creators","marketing teams","designers"]}


