# templates

name: Generate consensus-based answers using Claude, GPT, Grok and Gemini
author_name: Yehor EGMS
author_username: egm-systems
categories: []
created_at: 2026-01-05T09:09:59.191Z
updated_at: 2026-01-05T09:09:59.191Z
url: https://n8n.io/workflows/12471
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  The original LLM Council concept was introduced by Andrej Karpathy and published as an open-source repository demonstrating multi-model consensus and ranking.
  This workflow is my adaptation of that original idea, reimplemented and structured as a production-ready n8n template. Original repository - https://github.com/karpathy/llm-council

  This n8n template implements the LLM Council pattern: a single user question is processed in parallel by multiple large language models, independently evaluated by peer models, and then synthesized into one high-quality, consensus-driven final answer.
  It is designed for use cases where answer quality, balance, and reduced single-model bias are critical.

  📌 Section 1: Trigger & Input

  ⚡ When Chat Message Received (Chat Trigger)
  Purpose:
  Receives a user’s message and initiates the entire workflow.

  How it works:

  A user sends a chat message

  The message is stored as the Original Question

  The same input is forwarded simultaneously to multiple LLM pipelines

  Why it matters:
  Provides a clean, unified entry point for all downstream multi-model logic.

  📌 Section 2: Stage 1 — Parallel LLM Responses

  🤖 Basic LLM Chains (x4)
  Models used:

  Anthropic Claude

  OpenAI GPT

  xAI Grok

  Google Gemini

  Purpose:
  Each model independently generates its own response to the same question.

  Key characteristics:

  Identical prompt structure for all models

  Independent reasoning paths

  No shared context between models

  Why it matters:
  Produces diverse perspectives, reasoning styles, and solution approaches.

  📌 Section 3: Stage 2 — Response Anonymization

  🧾 Set Nodes (Response A / B / C / D)
  Purpose:
  Stores model outputs in an anonymized format:

  Response A

  Response B

  Response C

  Response D

  Why it matters:
  Prevents evaluator models from knowing which LLM authored which response, reducing bias during evaluation.

  📌 Section 4: Stage 3 — Peer Evaluation & Ranking

  📊 Evaluation Chains (Claude / GPT / Grok / Gemini)
  Purpose:
  Each model acts as a reviewer and:

  Analyzes all four anonymized responses

  Describes strengths and weaknesses of each

  Produces a strict FINAL RANKING from best to worst

  Ranking format (strict):

  FINAL RANKING:
  Response B
  Response A
  Response D
  Response C


  Why it matters:
  Creates multiple independent quality assessments from different model perspectives.

  📌 Section 5: Stage 4 — Ranking Aggregation

  🧮 Code Node (JavaScript)
  Purpose:
  Aggregates all peer rankings by:

  Parsing ranking positions

  Calculating average position per response

  Counting evaluation occurrences

  Sorting responses by best average score

  Output includes:

  Aggregated rankings

  Best response label

  Best average score

  Why it matters:
  Transforms subjective rankings into a structured, quantitative consensus.

  📌 Section 6: Stage 5 — Final Consensus Answer

  🧠 Chairman LLM Chain
  Purpose:
  One model acts as the Council Chairman and:

  Reviews all original responses

  Considers peer rankings and aggregated scores

  Identifies consensus patterns and disagreements

  Produces a single, clear, high-quality final answer

  Why it matters:
  Delivers a refined response that reflects collective model intelligence rather than a simple average.

  📊 Workflow Overview
  Stage	Node / Logic	Purpose
  1	Chat Trigger	Receive user question
  2	LLM Chains	Generate independent responses
  3	Set Nodes	Anonymize outputs
  4	Evaluation Chains	Peer review & ranking
  5	Code Node	Aggregate rankings
  6	Chairman LLM	Final synthesized answer
  🎯 Key Benefits

  🧠 Multi-model intelligence — avoids reliance on a single LLM
  ⚖️ Reduced bias — anonymized peer evaluation
  📊 Quality-driven selection — ranking-based consensus
  🔁 Modular architecture — easy to add or replace models
  🌍 Language-flexible — input and output languages configurable
  🧩 Production-ready logic — clear stages, deterministic ranking

  🚀 Ideal Use Cases

  High-stakes decision support

  Complex technical or architectural questions

  Strategy and research synthesis

  AI assistants requiring higher trust and reliability

  Comparing and selecting the best LLM-generated answers

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","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/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.lmChatXAiGrok","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.slack","n8n-nodes-base.whatsApp","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 9548 characters]

metadata_json:
  {"categories":["AI/ML","Data Processing"],"complexity":"medium","use_cases":["generate multi-model consensus","compare LLM responses","rank answers by model agreement"],"estimated_setup_minutes":5,"required_services":["Anthropic","xAI","OpenRouter","Google AI"],"key_features":["parallel model comparison","voting system for answer selection","confidence score calculation"],"target_audience":["AI engineers","developers"]}


name: Track portfolio performance and risk using Google Sheets and Alpha Vantage
author_name: Rahul Joshi
author_username: rahul08
categories: []
created_at: 2026-01-05T14:41:03.439Z
updated_at: 2026-01-05T14:41:03.439Z
url: https://n8n.io/workflows/12487
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  📄 Description
  This workflow helps users track and understand the performance of their stock portfolio in an automated and structured way. It reads portfolio holdings from Google Sheets, fetches the latest market prices, calculates key performance metrics, and updates the results back into the same sheet. In addition to standard return calculations, the workflow also classifies each holding based on overall performance and risk, making the output more actionable and easier to interpret.
  The workflow is designed for investors who want a simple, repeatable way to monitor portfolio performance without manual calculations.
  ⚙️ What This Workflow Does
  Reads portfolio holdings (stock, buy price, quantity, buy date) from Google Sheets
  Fetches daily stock price data using Alpha Vantage
  Calculates key metrics:
    Invested Value
     Current Value
    Profit & Loss (P&L)
     P&L Percentage
     CAGR
     Maximum Drawdown
  Classifies each holding as Healthy, Watch, or Risk based on return and drawdown
  Updates the same Google Sheet with the latest results
  Runs automatically on a schedule
  ✅ Key Benefits
  Eliminates manual portfolio tracking and calculations
  Provides clear performance and downside risk visibility
  Adds a simple decision layer through portfolio status classification
  Keeps all portfolio data in one place (Google Sheets)
  Dashboard-ready output for further analysis or visualization
  🧩 Features
  Scheduled portfolio evaluation
  Daily market price data from Alpha Vantage
  Deterministic, explainable financial calculations
  Simple risk and performance classification logic
  Google Sheets-based input and output
  Clean, update-in-place data handling (no duplicate rows)
  🔐 Requirements
  Alpha Vantage API key (for market price data)
  Google Sheets OAuth credentials
  An n8n instance (cloud or self-hosted)
  🎯 Target Audience
  Retail investors tracking long-term portfolios
  Finance teams maintaining internal portfolio dashboards
  Automation builders creating investment-related workflows
  Users looking for a simple, explainable portfolio monitoring setup

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.errorTrigger","n8n-nodes-base.gmail"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Data Processing","Finance"],"complexity":"medium","use_cases":["track stock performance","calculate portfolio returns","assess risk metrics","automate financial reports"],"estimated_setup_minutes":15,"required_services":["Google Sheets"],"key_features":["automated data fetching","performance classification","risk assessment","batch processing"],"target_audience":["investors","analysts"]}


author_name: Open Paws
author_username: openpaws
categories: []
created_at: 2026-01-05T23:42:56.709Z
updated_at: 2026-01-05T23:42:56.709Z
url: https://n8n.io/workflows/12502
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
name:
  Analyze failed workflows with Claude via OpenRouter and log to Sheets with Slack, Email, Discord alerts

description:
  Who is this for

  This workflow is designed for n8n users who manage multiple production workflows and want to:
  Receive intelligent, actionable error alerts instead of raw stack traces
  Understand root causes without manually debugging every failure
  Prevent alert fatigue from repeated similar errors
  Maintain a searchable log of all workflow errors

  It's ideal for animal advocacy organizations, campaign coordinators, and activists running mission-critical automation workflows for outreach, volunteer coordination, or campaign monitoring.

  What it does

  When any workflow in your n8n instance fails, this agent automatically:
  Captures the error details including workflow name, failed node, error message, and stack trace
  Uses AI (via OpenRouter/Claude) to analyze the error and suggest root causes and fixes
  Generates a unique error signature for deduplication
  Logs the error with AI analysis to Google Sheets for historical tracking
  Checks for recent duplicate errors to prevent alert fatigue
  Sends enriched notifications through your choice of Slack, Discord, Email, or Webhook

  The AI analysis includes root cause identification, error chain tracing, specific fix recommendations, and a confidence score indicating how certain the analysis is.

  How to set up

  Import the workflow into your n8n instance
  Configure credentials for:
     OpenRouter API for AI analysis
     Google Sheets for error logging
     Notification channels you want to use (Slack, Discord, Gmail, or Webhook URL)
  Create a Google Sheet with columns matching the log fields
  Update the receiver email addresses in the "Normalize Error Payload" node
  Enable the workflow
  Set this workflow as the error handler for other workflows you want to monitor

  Requirements

  OpenRouter API key (for AI-powered error analysis)
  Google Sheets OAuth2 credentials
  At least one notification channel configured (Slack, Discord, Gmail, or custom webhook)
  n8n instance with Error Trigger capability

  How to customize

  Change the AI model**: Edit the OpenRouter Chat Model node to use a different LLM
  Adjust alert fatigue settings**: Modify the lookback count and time window in the "Check Alert Fatigue" code node
  Switch logging backend**: Replace the Google Sheets node with PostgreSQL, Notion, or any other storage
  Add notification channels**: The workflow sends to multiple channels in parallel - add or remove as needed
  Customize email recipients**: Update the receiver emails array in the normalize payload node

nodes_used:
  ["n8n-nodes-base.errorTrigger","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.googleSheets","n8n-nodes-base.slack","n8n-nodes-base.discord","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 11928 characters]

metadata_json:
  {"categories":["DevOps"],"complexity":"medium","use_cases":["error monitoring","root cause analysis"],"estimated_setup_minutes":30,"required_services":["OpenRouter","Google Sheets","Slack","Discord","Email"],"key_features":["AI-driven error analysis","multi-channel alerting"],"target_audience":["n8n operators","IT administrators"]}


name: Research organizations with GPT‑5, Gemini, CourtListener, LegiScan and OSINT web sources
author_name: Open Paws
author_username: openpaws
categories: []
created_at: 2026-01-06T00:06:19.017Z
updated_at: 2026-01-06T00:06:19.017Z
url: https://n8n.io/workflows/12506
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Who is this for

  This workflow is designed for researchers, investigators, and analysts who need to:
  Build comprehensive profiles of organizations from public sources
  Research court cases, legislation, and government documents related to companies
  Verify company information across multiple authoritative databases
  Conduct due diligence or competitive intelligence research

  It's ideal for animal advocacy organizations researching factory farms and slaughterhouses, investigative journalists exposing animal cruelty, legal teams building cases against animal agriculture companies, and activists conducting corporate campaigns.

  What it does

  This multi-phase OSINT agent systematically researches organizations:
  Discovery phase: Searches multiple databases to find all relevant records
     CourtListener for federal and state court cases
     LegiScan for related legislation across all states
     DocumentCloud for government documents and reports
     Serper for web articles, news, and academic papers
  Verification phase: Confirms discovered records actually relate to the target company (not similar names)
  Prioritization phase: Scores and selects the most relevant items for deep analysis
  Retrieval phase: Fetches full text of selected court opinions, bills, and documents
  Analysis phase: Synthesizes findings into strategic insights
  Verification phase: Checks the final report against sources for accuracy

  The workflow prevents false positives by verifying company name matches, domain connections, and jurisdiction consistency.

  How to set up

  Import the workflow into your n8n instance
  Configure the required API credentials:
     CourtListener API for court case searches
     LegiScan API for legislation searches
     Serper API for web searches
     Jina AI API for article content extraction
     OpenRouter API for AI analysis
  Test with a well-known company to verify API connections
  Activate the workflow

  Example usage

  {
    "companyName": "Tyson Foods",
    "companyDomain": "tysonfoods.com",
    "reportGoal": "Identify environmental violations, labor disputes, and regulatory actions in the past 5 years"
  }

  Requirements

  CourtListener API key (free tier available)
  LegiScan API key
  Serper API key
  Jina AI API key
  OpenRouter API key

  How to customize

  Add data sources**: Integrate SEC filings, USDA inspection reports, EPA violations databases, or OSHA records
  Adjust verification criteria**: Modify the company matching logic for subsidiaries or DBAs (useful for tracking complex corporate structures in animal agriculture)
  Focus research scope**: Limit searches to specific jurisdictions or time periods relevant to your campaign
  Change output format**: Customize the final report structure for campaign briefings or legal filings
  Add export options**: Connect to document generation tools for formatted reports to share with coalition partners

nodes_used:
  ["n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.toolHttpRequest","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.jinaAiTool","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.vectorStoreWeaviate","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolHttpRequest","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.respondToWebhook","n8n-nodes-base.set","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.httpRequestTool","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.webhook"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Research","Legal Due Diligence"],"complexity":"complex","use_cases":["build organization profiles","research court cases","verify company information","conduct due diligence","gathering OSINT data"],"estimated_setup_minutes":300,"required_services":["OpenRouter","GPT-5","Gemini API","CourtListener","LegiScan","Jina AI","web scraping services"],"key_features":["multi-source data aggregation","legal document analysis","automated research reports","contextual decision making","OSINT verification"],"target_audience":["researchers","investigative journalists","auditors"]}


name: Build person OSINT profiles using Humantic AI, Hunter, CourtListener and GPT-5
author_name: Open Paws
author_username: openpaws
categories: []
created_at: 2026-01-06T00:07:03.033Z
updated_at: 2026-01-06T00:07:03.033Z
url: https://n8n.io/workflows/12507
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Who is this for

  This workflow is designed for sales professionals, recruiters, and researchers who need to:
  Build comprehensive profiles of individuals from public sources
  Understand communication and personality styles before outreach
  Find verified contact information
  Research legal and public record history for individuals

  It's ideal for animal advocacy campaigns targeting corporate decision-makers, researchers profiling legislators on animal welfare issues, and activists preparing for meetings with executives at companies being asked to adopt animal welfare policies.

  What it does

  This multi-source OSINT agent creates comprehensive individual profiles:
  Personality analysis: Uses Humantic AI to analyze LinkedIn profiles for communication preferences, personality traits, and engagement recommendations
  Contact discovery: Uses Hunter.io to find and verify professional email addresses
  Legal research: Searches CourtListener for any court cases involving the individual
  Legislation involvement: Checks LegiScan for any legislative activity or testimony
  Document search: Searches DocumentCloud for government documents mentioning the person
  Web research: Uses Serper to find news articles, publications, and public appearances
  Synthesis: Combines all findings into an actionable intelligence report

  The workflow waits for Humantic AI profile generation (45 seconds) before retrieving the complete personality analysis.

  How to set up

  Import the workflow into your n8n instance
  Configure the required API credentials:
     Humantic AI API for personality analysis
     Hunter API for email finding
     CourtListener API for court case searches
     LegiScan API for legislation searches
     Serper API for web searches
     Jina AI API for content extraction
     OpenRouter API for AI synthesis
  Test with a public figure to verify all integrations
  Activate the workflow

  Example usage

  {
    "firstName": "John",
    "lastName": "Davis",
    "companyName": "Smithfield Foods",
    "companyDomain": "smithfieldfoods.com",
    "linkedinURL": "https://linkedin.com/in/johndavis",
    "reportGoal": "Prepare for corporate campaign meeting - understand decision-making authority, communication style, and any public statements on animal welfare"
  }

  Requirements

  Humantic AI API key
  Hunter API key
  CourtListener API key
  LegiScan API key
  Serper API key
  Jina AI API key
  OpenRouter API key

  How to customize

  Skip personality analysis**: Remove the Humantic AI nodes if you only need factual research
  Add social media**: Integrate Twitter/X or other social platform analysis to track public statements on animal issues
  Extend contact finding**: Add additional email verification or phone number lookup services
  Customize report format**: Adjust the final synthesis prompt for campaign briefings, legislator profiles, or corporate target research
  Add campaign database integration**: Connect output directly to your advocacy CRM or campaign tracking system
  Batch processing**: Wrap the workflow to process multiple decision-makers from a target company list

nodes_used:
  ["n8n-nodes-base.humanticAi","n8n-nodes-base.humanticAi","n8n-nodes-base.hunter","n8n-nodes-base.set","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.toolHttpRequest","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.jinaAiTool","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.vectorStoreWeaviate","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.respondToWebhook","n8n-nodes-base.if","n8n-nodes-base.set","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.webhook","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
  [encoded data, 45540 characters]

metadata_json:
  {"categories":["Communication","Data Processing","Marketing"],"complexity":"complex","use_cases":["Generate OSINT profiles","Contact verification","Personality analysis","Public record research"],"estimated_setup_minutes":120,"required_services":["Humantic AI","Hunter","CourtListener","OpenRouter"],"key_features":["Aggregates public data sources","AI-powered personality profiling","Legal history lookup","Automated outreach strategy"],"target_audience":["sales professionals","recruiters","researchers"]}


name: Research US legal regulations with CourtListener, LegiScan, OpenRouter and web search
author_name: Open Paws
author_username: openpaws
categories: []
created_at: 2026-01-06T00:07:51.101Z
updated_at: 2026-01-06T00:07:51.101Z
url: https://n8n.io/workflows/12508
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Who is this for

  This workflow is designed for legal professionals, policy analysts, and compliance teams who need to:
  Research case law, legislation, and regulatory developments on specific topics
  Build comprehensive legal intelligence reports from authoritative sources
  Track enforcement trends and regulatory patterns
  Support litigation strategy with thorough background research

  It's ideal for animal law attorneys, advocacy organizations tracking animal welfare legislation, policy teams monitoring ag-gag laws and farm animal protection bills, and researchers building legal cases against animal cruelty.

  What it does

  This specialized legal research agent conducts comprehensive US legal and regulatory research:
  Discovery phase: Casts a wide net across legal databases
     CourtListener for federal and state court opinions and dockets
     LegiScan for legislation across all 50 states
     DocumentCloud for government enforcement documents
     Serper for legal analysis, news, and academic papers
  Prioritization phase: AI evaluates all discovered items and selects the most relevant (3-10 items) with scoring rationale
  Retrieval phase: Fetches complete text of prioritized court opinions, bill text, and documents
  Analysis phase: Synthesizes patterns, contradictions, and strategic insights
  Verification phase: Validates factual claims against source documents with hallucination detection

  The verification phase uses a specialized legal-focused prompt that distinguishes between legitimate legal strategy (which should never be flagged) and actual factual errors like wrong case citations or non-existent statutes.

  How to set up

  Import the workflow into your n8n instance
  Configure the required API credentials:
     CourtListener API for case law searches
     LegiScan API for legislation searches
     Serper API for web searches
     Jina AI API for article extraction
     OpenRouter API for AI analysis
  Test with a well-documented legal topic to verify integrations
  Activate the workflow

  Example usage

  {
    "prompt": "Research the current legal challenges to California Proposition 12 (farm animal confinement standards), including constitutional commerce clause arguments and enforcement status"
  }

  Requirements

  CourtListener API key (free tier available)
  LegiScan API key
  Serper API key
  Jina AI API key
  OpenRouter API key

  How to customize

  Add jurisdiction filters**: Limit searches to specific federal circuits or states with active animal welfare legislation
  Adjust time ranges**: Focus on recent developments or historical case law in animal protection
  Extend source types**: Add USDA enforcement records, state animal cruelty databases, or international animal law sources
  Modify verification strictness**: Adjust the hallucination detection threshold for legal accuracy
  Create specialized variants**: Fork for specific areas (ag-gag laws, farmed animal welfare, animal testing regulations, wildlife protection)
  Add citation formatting**: Post-process reports to use proper legal citation formats (Bluebook, etc.)
  Integrate with legal tools**: Connect to Clio, case management systems, or your organization's legal database

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metadata_json:
  {"categories":["Legal Research","Compliance","Policy Monitoring"],"complexity":"medium","use_cases":["Research case law","Build legal reports","Track enforcement trends","Support litigation strategy"],"estimated_setup_minutes":15,"required_services":["OpenRouter","LegiScan","CourtListener","Web Search"],"key_features":["Multi-source research integration","AI-powered summarization","Structured output parsing","Conditional logic for case filtering"],"target_audience":["legal professionals","policy analysts","compliance teams"]}


name: Manage your WooCommerce store with OpenAI and MCP-powered AI assistant
author_name: SpaGreen Creative
author_username: spagreen
categories: []
created_at: 2026-01-06T10:19:29.970Z
updated_at: 2026-01-06T10:19:29.970Z
url: https://n8n.io/workflows/12516
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Who it's for
  This n8n workflow is designed for WooCommerce store owners and e-commerce managers who want to automate their store operations through an intelligent AI assistant. The workflow creates a conversational interface that can manage products, process orders, handle customers, and provide store analytics through natural language commands.

  Features
  Intelligent AI Assistant**: Powered by OpenAI with specialized system prompts for e-commerce operations
  WooCommerce Integration: Complete MCP (Model Context Protocol) server implementation for seamless **WooCommerce REST API operations
  Product Management**: Create, update, search, retrieve, and delete products automatically
  Order Processing**: Create, update, retrieve, and manage orders including fulfillment status
  Customer Management**: Create, update, retrieve, search, and delete customer information
  Context-Aware Automation: Uses conversation history and **WooCommerce data to minimize user input requirements

  Requirements
  WooCommerce API Keys (Consumer Key & Consumer Secret): For accessing your **WooCommerce store data and operations
  OpenAI API Credentials**: For powering the AI assistant
  Notification Service Credentials**:
    Discord Bot API, Telegram Bot API, Rapiwa API (for WhatsApp), Gmail OAuth2
  Configure Credentials
  WooCommerce API Keys**: Configure with proper permissions (read/write) for your store from the WooCommerce admin panel
  OpenAI API**: Set up with appropriate model access (gpt-4 or similar models)
  Notification Services**: Configure each service with proper API keys and target IDs

  Important Notes
  MCP Server Setup: The workflow includes a **WooCommerce MCP Server that must be properly configured for production use
  Tool Selection: The MCP Client includes specific **WooCommerce tools that can be enabled/disabled based on requirements
  System Prompt**: The AI assistant is configured with specialized e-commerce guidelines that can be customized
  Confirmation Requirements**: Irreversible actions like deletions will require confirmation
  Rate Limiting: The workflow includes appropriate delays to prevent **WooCommerce API rate limiting
  Notification Content**: All notifications include a standard success message that can be customized

  Production Deployment for MCP Server
  To deploy this workflow in production

  Support & Help
  WhatsApp**: Chat on WhatsApp
  Discord**: SpaGreen Community
  Facebook Group**: SpaGreen Support
  Website**: https://spagreen.net
  Developer Portfolio**: Codecanyon SpaGreen

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name: Get AI crypto price analysis via Telegram using GPT-4o-mini and TwelveData
author_name: Rahul Joshi
author_username: rahul08
categories: []
created_at: 2026-01-07T14:56:07.003Z
updated_at: 2026-01-07T14:56:07.003Z
url: https://n8n.io/workflows/12552
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  📊 Description
  Automate real-time cryptocurrency analysis by turning Telegram messages into professional, AI-generated market reports. 📈🤖 This workflow listens to user queries in Telegram, classifies intent using AI, fetches recent OHLC price data, and generates clear, structured crypto insights covering short-term and weekly trends. Each response is formatted for mobile-friendly Telegram delivery with key metrics, insights, and disclaimers. Ideal for crypto communities, analysts, and bot builders who want instant, reliable market analysis without manual charting. 🚀📊
  🔁 What This Template Does
  1️⃣ Listens for incoming Telegram messages in real time. 💬
   2️⃣ Extracts the user’s query text and chat ID. 🧾
   3️⃣ Uses AI to classify intent (price check, overview, trend analysis). 🤖
   4️⃣ Identifies the requested crypto symbol (BTC, ETH, etc.). 🔍
   5️⃣ Fetches 1-hour OHLC price data from CoinMarketCap/TwelveData. 📊
   6️⃣ Compares current price with 24h and 7d historical levels. ⏱️
   7️⃣ Evaluates volume and short-term market strength. 📈
   8️⃣ Generates a structured AI market analysis with confidence scoring. 🧠
   9️⃣ Formats the analysis into a clean, Telegram-friendly message. ✉️
   🔟 Sends the final report directly back to the user in Telegram. 📲
  ⭐ Key Benefits
  ✅ Delivers instant crypto analysis inside Telegram
   ✅ Eliminates manual chart reading and calculations
   ✅ Uses AI for consistent, structured market insights
   ✅ Mobile-friendly responses with key metrics
   ✅ Supports multiple crypto symbols on demand
   ✅ Ideal for bots, communities, and trading tools
  🧩 Features
  Telegram Bot trigger and message handling
  AI intent classification and symbol extraction
  Real-time OHLC price data retrieval
  AI-based price trend and volume analysis
  Structured JSON output for reliability
  Telegram-optimized message formatting
  Confidence scoring and risk disclaimers
  Built-in error handling with email alerts
  🔐 Requirements
  Telegram Bot API token
  OpenAI API key (GPT-4o-mini recommended)
  CoinMarketCap or TwelveData API key
  Gmail OAuth2 credentials (for error alerts)
  n8n instance with AI nodes enabled
  🎯 Target Audience
  Crypto traders and analysts
  Telegram bot builders
  Crypto communities and channels
  Fintech and trading platforms
  Automation teams building market insight bots

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metadata_json:
  {"categories":["AI/ML","Communication","Data Processing"],"complexity":"medium","use_cases":["Generate crypto market reports","Classify user intents","Fetch real-time OHLC data","Format mobile-friendly alerts"],"estimated_setup_minutes":45,"required_services":["Telegram","OpenAI (GPT-4o-mini)","TwelveData"],"key_features":["Real-time price analysis","AI-driven content generation","Message intent classification","Structured data parsing","Mobile-optimized responses"],"target_audience":["crypto traders","community managers","developers"]}


name: Conversational analytics with Google Sheet and C1 by Thesys
author_name: Billy Christi
author_username: billy
categories: []
created_at: 2026-01-08T01:37:18.231Z
updated_at: 2026-01-08T01:37:18.231Z
url: https://n8n.io/workflows/12565
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Conversational analytics with Google Sheet and C1 by Thesys
  Turn any Google Sheet into a chat-powered dashboard. Ask questions in plain English and get interactive charts, tables, and UI (not just text) powered by C1 by Thesys.
  Outcome: faster insights from spreadsheet data. No filters, pivot tables, or manual chart building.
  Check out a working demo of this template here.

  Example Use Cases
  You can use this setup for many real-world scenarios, such as:
  Lead Tracking
  Upload your leads data to Google Sheets
  Ask questions like:
    “How many new leads came from LinkedIn?”
    “Which region generated the most leads?”

  Marketing Campaign Analysis
  Store campaign performance data in a sheet
  Ask:
    “Which campaign had the highest conversion rate?”
    “Compare email vs paid ads performance”

  How it works
  User sends a prompt
  C1 model based on prompt will use CoinGecko MCP to fetch live data
  C1 Model generates a UI Schema Response
  Schema is rendered as UI using Thesys GenUI SDK on the frontend

  Setup
  Make sure you have the following:
  1. Thesys API Key
  You’ll need an API key to authenticate and use Thesys services.
  👉 Get your key here  

  2. Google Sheet as a Data Source
  Prepare a Google Sheet that contains your data:
  Column headers in the first row
  Clean, structured data (no merged cells)
  Example columns:
    date
    campaign_name
    leads
    cost

  Facing setup issues?
  If you get stuck or have questions:
  💬 Join the Thesys Community  
  📧 Email support:  support@thesys.dev

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

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metadata_json:
  {"categories":["Data Processing","Business Intelligence"],"complexity":"medium","use_cases":["Chat-based lead analysis","Interactive spreadsheet queries","Plain English data exploration"],"estimated_setup_minutes":15,"required_services":["Google Sheets","Thesys C1"],"key_features":["Natural language data querying","Visual insight generation","Turn-key chat dashboard"],"target_audience":["Business analysts","Data analysts"]}


name: Pick a Topic & Auto-Publish Translated Content on Multiple Social Media Platform
author_name: SpaGreen Creative
author_username: spagreen
categories: []
created_at: 2026-01-08T05:22:14.176Z
updated_at: 2026-01-08T05:22:14.176Z
url: https://n8n.io/workflows/12571
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Who it's for
  This n8n workflow is designed for content creators, digital marketers, and social media managers who want to automate their entire content creation and publishing process across multiple platforms. It provides a complete end-to-end system capable of taking a single specific idea and automatically generating a full piece of content from it—complete with images, translations, and platform-optimized formatting. The workflow then publishes the final content to WordPress, Facebook, LinkedIn, and Telegram.

  Features
  Multi-platform publishing:** WordPress, Facebook, LinkedIn, Telegram
  AI-powered content generation using OpenAI (LangChain):* Can generate a *full article or content piece from a single specific idea or topic**
  Multi-language support:** Automatic translation via Google Translate API
  Automatic image processing:** Resizing, optimization, and WordPress upload
  Google Sheets integration:** For topic management, content queueing, and status tracking
  Notifications:** Send updates via Discord, Telegram, WhatsApp, and Gmail
  Flexible workflow triggers:** Supports both manual form submissions and automated scheduled publishing

  Requirements
  OpenAI API access for content generation
  Google Translate API credentials
  WordPress API access
  Social media API credentials (Facebook, Telegram, LinkedIn)
  Google Sheets OAuth2 credentials
  Google Drive access for image storage

  Configure Credentials
  Google APIs**: Configure Google Sheets, Google Drive, and Google Translate with proper OAuth2 credentials
  OpenAI API**: Set up with appropriate model access (gpt-4.1-mini)
  WordPress API**: Configure with your WordPress site credentials
  Social Media APIs**: Set up each platform with proper API keys and target IDs
  Notification Services**: Configure each service with proper API keys and target IDs

  Important Notes
  Form captures topic, type, user, word count, company info, domain, language, and image
  AI content generation uses customizable prompts
  Images resized up to 5000x5000 px before upload
  Content can be translated via Google Translate API
  Workflow publishes text and image posts across platforms
  Google Sheets tracks content status in real-time

  Support & Help
  WhatsApp**: Chat on WhatsApp
  Discord**: SpaGreen Community
  Facebook Group**: SpaGreen Support
  Website**: https://spagreen.net
  Developer Portfolio**: Codecanyon SpaGreen

nodes_used:
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metadata_json:
  {"categories":["Marketing"],"complexity":"medium","use_cases":["generate content from topic","auto translate and format","publish cross-platform","create social media images","informally track campaign results"],"estimated_setup_minutes":45,"required_services":["Google Drive","WordPress","Facebook Graph API","LinkedIn API","Spreadsheets"],"key_features":["AI-powered content generation","multi-language translation support","platform-specific formatting","automated image creation","multi-platform publishing"],"target_audience":["content creators","digital marketers","social media managers"]}


name: Generate AI market research reports from NewsAPI and competitor sites to Notion, Sheets and Slack
author_name: sato rio
author_username: riorio
categories: []
created_at: 2026-01-08T08:01:11.947Z
updated_at: 2026-01-08T08:01:11.947Z
url: https://n8n.io/workflows/12581
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Generate market research reports from news and competitor sites to Notion and Slack

  This workflow automates market research and competitive intelligence by collecting industry news and competitor website updates, analyzing them with AI, and publishing structured insights to Notion and Slack.
  It replaces manual monitoring and summarization with a repeatable, scalable workflow suitable for daily or weekly use.

  Who’s it for

  Marketing teams** who want to track industry trends and competitor messaging in one place
  Product managers** looking for early signals to inform roadmap and prioritization decisions
  Founders and analysts** who need automated market briefings without manual research

  How it works

  A scheduled trigger starts the workflow (daily by default).
  Industry news is fetched via NewsAPI while competitor websites are scraped in parallel.
  All collected content is consolidated and sent to OpenAI (GPT-4o) for analysis.
  The AI generates a structured report including trends, SWOT insights, and recommended actions.
  The full Markdown report is saved to a Notion database, and an executive summary is posted to Slack.
  If any API call or scraping step fails, an error notification is sent to Slack.

  How to set up

  Add API credentials for OpenAI, NewsAPI, Notion, and Slack.
  Configure keywords and competitor URLs in the Research Configuration node.
  Select your Notion database and Slack channels in the relevant nodes.

  Requirements

  OpenAI API key (GPT-4o access)
  NewsAPI account
  Notion and Slack accounts

  How to customize the workflow

  Change the trigger to run weekly or on demand
  Modify the AI prompt to focus on pricing, features, or specific competitors
  Add additional sources such as RSS feeds or more competitor sites

nodes_used:
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metadata_json:
  {"categories":["Marketing"],"complexity":"medium","use_cases":["Track competitor updates","Gather industry news","Monitor market trends","Summarize competitor messaging","Publish reports to Notion"],"estimated_setup_minutes":30,"required_services":["NewsAPI","Slack","Notion","Google Sheets"],"key_features":["Automated data collection from multiple sources","AI-powered content summarization","Multi-channel reporting output","Scheduled execution with flexible frequency","Error handling and retry mechanisms"],"target_audience":["marketing teams","competitive intelligence analysts","market researchers"]}


name: Generate Instagram news carousels from RSS feeds using GPT-4o
author_name: Pixril
author_username: tani07
categories: []
created_at: 2026-01-08T15:00:54.398Z
updated_at: 2026-01-08T15:00:54.398Z
url: https://n8n.io/workflows/12587
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Overview
  This workflow deploys a fully autonomous "Viral News Agency" inside your n8n instance.

  Unlike simple auto-posters, this is a comprehensive content production pipeline. It acts as a 24/7 news monitor that scrapes viral stories, rewrites them into educational scripts using GPT-4o, designs professional 10-slide carousels, and publishes them directly to Instagram Business—completely on autopilot.

  Key Features
  Dual-Engine Architecture:* The unique "Hybrid Core" lets you choose between *Free (Gotenberg/Docker)* or *Paid (APITemplate)** image generation. Switch engines instantly via the Setup Form.
  Smart RSS Scraping:** Cleans incoming feeds and extracts high-quality "OG" (Open Graph) images to use as dynamic backgrounds.
  Viral Content Writer:** Uses a specialized AI Agent prompt to write "Hot Takes" and educational hooks, ensuring content is engaging, not just a summary.
  Auto-Publisher:** Handles the complex Meta API flow (Container &gt; Media Bundle &gt; Publish) to upload multi-slide carousels automatically.

  How it works
  Monitor: The News Source node watches your chosen RSS feeds (Tech, Sports, Politics, etc.) for breaking stories.
  Analyze: The AI Analyst (GPT-4o) reads the article, extracts the viral angle, and writes a full 10-slide script with captions and hashtags.
  Design: The workflow routes data to your chosen engine. It loops through the script 10 times to generate individual slides (Title, Content, Quotes).
  Publish: The agent uploads the images to Facebook's servers, bundles them into a Carousel Container, and publishes it live to your Instagram feed.

  Set up steps
  Estimated time: 10 minutes

  Credentials: Add your keys for OpenAI (Intelligence), Google Drive (Storage), and Facebook Graph API (Publishing).
  Instagram ID: Open the 3 Facebook nodes ("Create Container", "Carousel Bundle", "Publish Carousel") and replace the placeholder ID with your Instagram Business User ID.
  Image Engine:
      Option A (Free): Ensure you have a local Gotenberg instance running via Docker (docker run --rm -p 3000:3000 gotenberg/gotenberg:8).
      Option B (Paid): In the "Generate Image" node, add your APITemplate API Key and Template ID.
  Run: Use the "SETUP FORM" node to enter your RSS URL and Brand Name, then toggle to "Active"!

  About the Creator
  Built by Pixril. We specialize in building advanced, production-ready AI agents for n8n.
  Visit our website: https://www.pixril.com/
  Find more professional workflows in our shop: https://pixril.etsy.com

nodes_used:
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metadata_json:
  {"categories":["Marketing","Content Creation","Social Media Management"],"complexity":"medium","use_cases":["monitor viral stories","generate educational scripts","design carousel visuals","auto-publish to Instagram","scrape rss feeds"],"estimated_setup_minutes":15,"required_services":["GPT-4o","Instagram Business API","RSS Feed Providers","Google Drive","Facebook Graph API","n8n"],"key_features":["24/7 news monitoring","hybrid content generation (text + visual)","automated carousel assembly","viral story detection","educational script rewriting"],"target_audience":["Content Marketers","Social Media Managers","Digital Entrepreneurs"]}


name: Vet new Shopify leads with ZeroBounce and sync qualified contacts to HubSpot
author_name: ZeroBounce
author_username: zerobounce
categories: []
created_at: 2026-01-09T14:49:28.266Z
updated_at: 2026-01-09T14:49:28.266Z
url: https://n8n.io/workflows/12601
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Shopify to HubSpot: Advanced ZeroBounce Lead Vetting

  This workflow automates the transition of new Shopify customers into HubSpot, using ZeroBounce for multi-layer validation (Validation + AI Scoring).

  Results are also output to Google Sheets for review.

  🧩 Nodes used in this workflow
  ZeroBounce
  Shopify
  Hubspot
  Google Sheets (or alternative e.g. Data Table)

  💡 Key Benefits
  ✨ Zero-Waste Sync:** Only "Valid" or "High-Scoring" leads reach your CRM.
  🛡️ Credit Safety:** Internal checks ensure you never trigger an API call without credits.
  📊 Detailed Suppressions:** Every rejected lead is categorized by reason (e.g. Email Missing, Invalid, Low Score, or Insufficient credits).

  🚀 How it Works
  ⚡ Trigger & Verification: Activates on new Shopify customers and first checks if an email address is provided.
      Email present: Proceeds to credit check and validation
      Email missing: Customer details are added to Rejected output for review with reason 'Email missing'.
  💳 Credit Management: Before each ZeroBounce call, the workflow checks your account for sufficient credits to prevent node failures.
      Success: Proceeds to Stage 1 (Validation).
      Failure: Customer details are added to Rejected output for retry with reason 'Not enough credits'.
  ✔️ Stage 1: Email Validation: Validates the email address with ZeroBounce.
      Valid: Adds the result to Accepted output and creates a contact in HubSpot.
      Invalid: Logs to an n8n Data Table with the validation results and a reason for rejection for review.
      Catch-all: Proceeds to Stage 2 (Scoring).
  🎯 Stage 2: AI Email Scoring: For "Catch-all" emails, the workflow requests ZeroBounce AI Scoring.
      High Score (&gt;=9): Syncs to HubSpot.
      Medium/Low Score: Suppressed and added to an n8n Data Table with the assigned score for review.
  📤 Output Results:
      Accepted: Output validation and scoring results to Accepted and Hubspot
      Rejected Output validation and scoring results to Rejected.

  📋 Setup Requirements
  Shopify:** Connect via OAuth2 to watch for "Customer Created" events (Topic: customers/create).
  ZeroBounce:* Connect via API Key. *Create one here.
  HubSpot:** Connect via OAuth2 to create/update contacts for high-quality leads.
  Google Sheets:* Connect via OAuth2 to append/update rows in a Google Sheets worksheet. Alternatively, swap these nodes out with any other data storage node e.g. *n8n Data Table* or *Microsoft Excel**. The sheets/tables can be created with the headers:
      Accepted columns:
        ID,Email,First Name,Last Name,Accepted At,Accepted Reason,ZB Status,ZB Sub Status,ZB Free Email,ZB Did You Mean,ZB Account,ZB Domain,ZB Domain Age Days,ZB SMTP Provider,ZB MX Found,ZB MX Record,ZB Score
      Rejected columns
        ID,Email,First Name,Last Name,Rejected At,Rejected Reason,ZB Status,ZB Sub Status,ZB Free Email,ZB Did You Mean,ZB Account,ZB Domain,ZB Domain Age Days,ZB SMTP Provider,ZB MX Found,ZB MX Record,ZB Score

nodes_used:
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metadata_json:
  {"categories":["Marketing","Sales","Data Processing"],"complexity":"medium","use_cases":["verify lead quality before adding to CRM","filter new customers from Shopify to HubSpot","score and prioritize potential buyers","export validation results for manual review"],"estimated_setup_minutes":15,"required_services":["ZeroBounce","Shopify","HubSpot","Google Sheets"],"key_features":["automated lead validation via email verification service","AI-based scoring for lead qualification","conditional sync to CRM based on validation results","multi-step workflow logic with all passing criteria","data export to spreadsheet for review or auditing"],"target_audience":["sales teams","marketing managers","customer success coordinators"]}


name: RSVP Lead Scoring for Events with GPT, HubSpot & Slack
author_name: Milo Bravo
author_username: milobravo1
categories: []
created_at: 2026-01-10T14:48:56.257Z
updated_at: 2026-01-10T14:48:56.257Z
url: https://n8n.io/workflows/12618
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  RSVP Lead Scoring for Events with GPT, HubSpot & Slack

  Who is this for?
  Event organizers, RevOps teams, sales managers, and marketers running conferences, webinars, or meetups who want to automatically qualify RSVPs and turn attendees into revenue opportunities.

  What problem is this workflow solving?
  RSVP lead qualification is manual and slow:

  Reviewing 1000+ registrations takes hours
  Missing high-fit prospects (directors, founders) 
  No instant sales handoff or nurture segmentation
  Leads leak between events and CRM

  This workflow auto-scores RSVPs 0-100 and routes high-fits to sales instantly.

  What this workflow does

  Trigger**: Google Forms/Typeform RSVP webhook
  AI Scoring: GPT-4o-mini analyzes job title, company, intent → **0-100 fit score
  High Scorers (80+)**: HubSpot CRM contact + Slack "#sales: Director @ Acme (87) → Book now [Calendly]"
  Low Scorers**: Nurture sequence (email lists)
  Dashboard**: Google Sheets with scores, conversions tracked

  Setup (3 minutes)

  Forms**: Google Forms/Typeform → n8n webhook (copy/paste URL)
  AI**: OpenAI API key (GPT-4o-mini - cheap & fast)
  CRM**: HubSpot API key (works Free tier)
  Slack**: #sales channel + bot token

  Fully configurable—no code changes needed.

  How to customize to your needs

  Scoring**: Adjust GPT thresholds (80→90 for enterprise)
  CRM**: Swap HubSpot for Salesforce/Pipedrive
  Channels**: Add Teams/Email + multiple Slack rooms
  Events**: Multi-event scoring by form source
  Follow-up**: Auto-Calendly, SMS, or email sequences

  ROI:

  3x qualified leads** to sales team
  5x faster sales response** 
  40% less lead leakage** (proven 500+ runs)
  Zero manual qualification**

  Need help customizing?: 
  Contact me for consulting and support: LinkedIn / Message 

  Keywords: event RSVP, AI lead scoring, conference lead qualification, event lead gen RevOps, lead fit scoring.

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.hubspot","n8n-nodes-base.hubspot","n8n-nodes-base.slack","n8n-nodes-base.slack","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.webhook","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Marketing","DevOps","Data Processing","Communication"],"complexity":"medium","use_cases":["Automatically qualify event attendees","Identify high-value prospects from RSVPs","Route leads to sales teams","Trigger Slack notifications for new leads","Segment leads based on role or query responses"],"estimated_setup_minutes":25,"required_services":["HubSpot","Slack","OpenAI (GPT)","Spreadsheets (e.g., Google Sheets, Excel)"],"key_features":["AI-powered lead qualification","Dynamic lead scoring","Automated Slack notifications for sales","Integration with CRM systems","Real-time prospect segmentation"],"target_audience":["Event managers","RevOps professionals","Sales managers"]}


name: AI Event Feedback Analyzer with Google Forms, GPT, Slack & Docs
author_name: Milo Bravo
author_username: milobravo1
categories: []
created_at: 2026-01-10T16:34:58.414Z
updated_at: 2026-01-10T16:34:58.414Z
url: https://n8n.io/workflows/12621
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  AI Event Feedback Analyzer with Google Forms, GPT,  Slack & Docs

  Who is this for?
  Event planners, webinar hosts, conference organizers, and marketers who collect attendee feedback and want instant actionable insights without manual analysis.

  What problem is this workflow solving?
  Post-event feedback analysis is slow and manual:

  Sorting 100s of forms takes hours
  Missing sentiment patterns or testimonials
  No real-time team alerts or historical logs

  This workflow automates sentiment analysis + distribution across Slack and Google Docs.

  What this workflow does

  Trigger**: Google Forms → Sheets webhook (works with Typeform too)
  AI Analysis**: GPT-4o extracts: Sentiment score, key likes/improvements, golden quotes
  Slack Alert**: "#eventfeedback: 4.2/5 'Loved networking' → Action: More breaks"
  Google Docs Log**: Appends "{{Event}} Feedback Summary" with bullets + NPS trends
  Bonus**: 50+ responses → "Avg NPS 4.2 | Top 3 fixes ranked"

  Setup (3 minutes)

  Google Forms** → Sheets (native integration)
  Slack channel + OpenAI API key** (GPT-4o-mini recommended)
  Google Docs ID** (env var DOCS_ID)

  Fully configurable—no code changes needed.

  How to customize to your needs

  Forms**: Swap Google Forms for Typeform/Webhook
  AI**: Adjust sentiment thresholds or add custom categories
  Channels**: Add Teams/Email + multiple Slack rooms
  Metrics**: Track NPS, CSAT, or custom scores
  Scale**: Aggregate by event/date for multi-conference orgs

  ROI:

  30% faster feedback loops**
  15% NPS uplift** (proven 500+ runs)
  Zero manual analysis**

  Need help customizing?: 
  Contact me for consulting and support: LinkedIn / Message

  Keywords: event management, sentiment analysis, post-event feedback, conference feedback 

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name: Analyze domain keyword rankings and summarize with SE Ranking and GPT-4.1-mini
author_name: Ranjan Dailata
author_username: ranjancse
categories: []
created_at: 2026-01-11T04:16:14.581Z
updated_at: 2026-01-11T04:16:14.581Z
url: https://n8n.io/workflows/12631
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  This n8n workflow automates domain level keyword ranking analysis and enriches raw SEO metrics with AI-generated summaries. It combines structured keyword data from SE Ranking with natural-language insights produced by OpenAI, turning complex SERP datasets into actionable SEO intelligence.

  Who this is for?

  This workflow is designed for:

  SEO engineers and technical marketers
  Growth teams running programmatic SEO
  Agencies managing multi-domain keyword analysis
  Product teams building SEO analytics pipelines
  Developers using n8n for data enrichment and reporting

  If you work with keyword data and need machine-readable output plus human-readable insights, this workflow is for you.

  What this workflow does

  Accepts a target domain or URL, region, keyword type (organic/paid), and filters
  Fetches keyword ranking data from the SE Ranking Domain Keywords API
  Extracts metrics such as:

     Keyword positions
     Search volume & CPC
     Competition & difficulty
     SERP features & search intent
     Traffic estimates
  Uses OpenAI GPT-4.1-mini to generate:

     A comprehensive narrative summary
     A concise abstract overview
  Merges raw data and AI insights into a single enriched dataset
  Exports the final output as structured JSON for downstream use

  Setup

  Prerequisites

  Active SE Ranking API access
  OpenAI API key with GPT-4.1-mini enabled
  Running n8n instance (self-hosted or cloud)
  Basic understanding of keyword ranking metrics

  Configuration steps

  If you are new to SE Ranking, please signup on seranking.com

  Import the workflow JSON into n8n
  Configure credentials:

     SE Ranking using HTTP Header Authentication. Please make sure to set the header authentication as below. The value should contain a Token followed by a space with the SE Ranking API Key.



     OpenAI API (GPT-4.1-mini model)
  Open the Set the Input Fields node and define:

     target_site (domain or URL)
     source (region, e.g. us)
     type (organic or paid)
     limit, filters, and requested columns
  Verify the output as per the export data handling.

  Converts enriched SEO results into structured JSON output
  Creates binary data to support file-based exports
  Converts processed data into CSV format for easy analysis
  Inserts or updates records in Google Sheets for reporting
  Ensures data consistency across all export destinations
  Enables downstream automation, dashboards, and audits


  Click Execute Workflow

  How to customize this workflow to your needs

  You can easily adapt this workflow by:

  Switching between organic and paid keyword analysis
  Changing regions for international SEO tracking
  Modifying requested keyword columns and SERP filters
  Customizing the OpenAI prompt to generate:

    SEO action items
    Competitive insights
    Executive summaries
  Replacing file export with:

    Databases
    Dashboards
    Slack/Email alerts
    Data warehouses

  Summary

  This n8n template delivers a production ready SEO analytics pipeline that bridges structured SERP data with AI powered interpretation. By combining SE Ranking’s keyword intelligence with OpenAI driven summarization, it enables faster insights, better reporting, and scalable SEO decision making without manual analysis.

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name: Route and categorize Gmail emails to Slack with Llama 3 via OpenRouter
author_name: Intuz
author_username: intuz
categories: []
created_at: 2026-01-13T06:25:57.204Z
updated_at: 2026-01-13T06:25:57.204Z
url: https://n8n.io/workflows/12671
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  This n8n template from Intuz provides a complete and automated solution to transform your team's inbox management. 

  It acts as an intelligent agent that reads incoming Gmail messages, uses AI to determine their category, and automatically routes them to the correct Slack channel—even creating new channels on the fly for new topics.

  Who's this workflow for?
  Customer Support Teams
  Sales & Lead Management Teams
  Operations & Project Management Teams
  Any team that uses Slack as a central hub for communication and triaging tasks.

  How it works
  1. Monitor New Emails:
  The workflow continuously checks a specified Gmail account for new, unread emails. It automatically filters out spam, drafts, and duplicates.

  2. AI Categorization: 
  Each new email's subject and body are sent to an AI model (like Llama 3 via OpenRouter). The AI analyzes the content and assigns a category based on a predefined list (e.g., sales, marketing, accounts, internal).

  3. Find or Create Slack Channel: 
  The workflow then checks your Slack workspace to see if a channel corresponding to the AI's category already exists (e.g., #sales).

  4. Route the Email:
  If the channel exists: The workflow posts a formatted summary of the email, a link to the original message in Gmail, and a "Reply" button directly into the existing channel.
  If the channel does NOT exist: The workflow automatically creates a new public channel (e.g., #new-category), invites a designated user, and then posts the email summary.

  Key Requirements to Use This Template

  1. n8n Instance & Required Nodes:
  An active n8n account (Cloud or self-hosted).
  This workflow uses the official n8n LangChain integration (@n8n/n8n-nodes-langchain). If you are using a self-hosted version of n8n, please ensure this package is installed.

  2. Gmail Account: 
  An active Gmail account with API access enabled.

  3. Slack Workspace & App:
  A Slack workspace where you have permission to install apps.
  A Slack App with a Bot Token that has the following scopes: channels:read, channels:manage, chat:write, groups:write, and users:read.

  4. OpenRouter Account: 
  An account with OpenRouter to access various AI models like Llama 3. You will need an API key.

  Setup Instructions
  1. Gmail Configuration:
  In the "Capture Gmail Event" (Gmail Trigger) node, connect your Gmail account using OAuth2 credentials.

  2. OpenRouter AI Configuration:
  In the "OpenRouter Chat Model" node, create a new credential and add your OpenRouter API key.

  3. Slack Configuration:
  Create a Slack App: Go to api.slack.com/apps, create a new app, and install it to your workspace.
  Set Permissions: In your app's "OAuth & Permissions" settings, add the following Bot
  Token Scopes: channels:read, channels:manage, chat:write, groups:write, users:read. Reinstall the app to your workspace after adding them.
  Get Bot Token: Copy the "Bot User OAuth Token" (it starts with xoxb-).
  Connect in n8n: In all Slack nodes in the workflow, create a new credential and paste this Bot Token.
  Set User to Invite: In the "Invite a user to a channel" node, replace the placeholder User ID (U0A6ULM7CGK) with the Slack Member ID of the user you want to be automatically invited to new channels.

  4. Activate the Workflow:
  Save the workflow and toggle the "Active" switch to ON. Your intelligent email routing system is now live!

  Support
  If you need help setting up this workflow or require a custom version tailored to your specific use case, please feel free to reach out to the template author:

  Website: https://www.intuz.com/n8n-workflow-automation-templates
  Email: getstarted@intuz.com
  LinkedIn: https://www.linkedin.com/company/intuz
  Get Started: https://n8n.partnerlinks.io/intuz

  For Custom Worflow Automation
  Click here- Get Started

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name: Send AI revenue forecast alerts from HubSpot via Gmail, Slack and Sheets
author_name: Avkash Kakdiya
author_username: itechnotion
categories: []
created_at: 2026-01-13T07:16:33.202Z
updated_at: 2026-01-13T07:16:33.202Z
url: https://n8n.io/workflows/12674
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  How it works
  This workflow automatically generates an AI-powered revenue forecast whenever a new deal is created in HubSpot. It collects all active deals, standardizes key sales data, and sends it to an AI model for forecasting and risk analysis. The AI produces best, likely, and worst-case revenue scenarios along with actionable insights. Results are shared with stakeholders via Slack and Email and stored in Google Sheets for tracking.

  Step-by-step
  Step 1 : Collect & prepare HubSpot deals**
    HubSpot Trigger – Starts the workflow when a new deal is created in HubSpot.
    Get many deals – Fetches all active deals from the sales pipeline.
    Format HubSpot Data – Cleans and standardizes deal fields like amount, stage, probability, and region.
    Loop Over Items – Iterates through formatted deals to prepare them for AI analysis.

  Step 2 : Generate & distribute AI forecast**
    AI Revenue Forecast & Risk Analysis – Sends pipeline data to the AI model to generate revenue forecasts and insights.
    Groq Chat Model – Powers the AI analysis and produces structured forecasting output.
    Format AI response – Extracts key metrics, risks, and recommendations from the AI response.
    Send a message (Gmail) – Emails the revenue forecast report to stakeholders.
    Send a message (Slack) – Posts the forecast summary to a selected Slack channel.
    Append row in sheet – Logs forecast data and insights into Google Sheets.
    Wait – Adds a controlled pause before looping or completing the workflow.

  Why use this?
  Get real-time revenue forecasts triggered directly by CRM activity.
  Reduce manual pipeline analysis and reporting effort.
  Identify high-risk deals early with AI-driven insights.
  Keep leadership aligned through automated Slack and Email updates.
  Maintain a historical forecast log for audits and performance tracking.

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metadata_json:
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name: ⚡ Text → Viral Shorts | AI Video Studio in Telegram /w Setup Video
author_name: Joe V
author_username: joevenner
categories: []
created_at: 2026-01-13T15:08:40.590Z
updated_at: 2026-01-13T15:08:40.590Z
url: https://n8n.io/workflows/12682
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  🎬 AI Video Studio Bot - Telegram to YouTube Shorts, TikTok and Instagram Reels Automation

  Transform text into viral shorts — all from your phone 📱✨
  🎥 Watch It In Action



  🔗 Full Demo: youtu.be/OI_oJ_2F1O0

  🚀 What This Workflow Does

  Imagine having a full-stack AI video production studio in your pocket — no editing software, no dashboard hopping, no prompt engineering. Just pure creation magic through Telegram.

  This n8n workflow transforms Telegram into your personal AI video factory that:

  Your Message → AI Magic → Viral Short → Auto-Published
       ⏱️ 30 seconds          🎬 2-5 minutes       📤 Done!

  The Complete Pipeline:

  📱 Message Telegram Bot - Send text, image, or voice memo
  🤖 AI Prompt Generation - GPT-4 crafts perfect video prompts
  🎬 Video Creation - Veo 3, Sora 2, or Seedance generates your short
  📤 Auto-Upload - Instantly publishes to YouTube Shorts
  🔁 Extend & Iterate - One-tap video extension (Veo only)

  No manual work. No technical skills. No limits.

  💡 Why This Changes Everything

  | Traditional Way | This Workflow |
  |----------------|---------------|
  | ❌ Open 5+ platforms | ✅ One Telegram chat |
  | ❌ 30 min per video | ✅ 5 min per video |
  | ❌ Complex prompts needed | ✅ AI writes prompts for you |
  | ❌ Manual uploads | ✅ Auto-publishes everywhere |
  | ❌ Desktop only | ✅ Works from your phone |

  Result: Create 10+ YouTube Shorts during your lunch break 🚀

  🎨 Video Styles - Choose Your Vibe

  Control everything with simple Telegram commands:

  | Command | Style | Perfect For |
  |---------|-------|------------|
  | /general | 🎭 Creative Shorts | Product demos, hooks, viral content |
  | /lost | 👻 Found Footage | Mystery, horror, urban exploration |
  | /3d | 🎮 3D Objects | Talking products, explainers, memes |
  | /story | 📖 Emotional Stories | Multi-scene narratives, brand stories |

  No command? AI intelligently picks the best style for your message.

  🤖 AI Models - Pick Your Engine

  Choose your video generation model right from Telegram:

  Veo 3 / Veo 3 Fast ⚡
  Best for: Quick iterations, realistic scenes
  Speed: 2-3 minutes
  Unique: Video extension support

  Sora 2 🎬
  Best for: Cinematic quality, long sequences
  Speed: 4-5 minutes
  Unique: Best motion consistency

  Seedance 1.5 Pro 🌊
  Best for: Artistic effects, fluid motion
  Speed: 3-4 minutes
  Unique: Stylized aesthetics

  Select directly in-chat with interactive buttons!

  ⚡ Power Features

  🎯 Smart Video Generation
  AI analyzes your message intent
  Generates optimal prompts automatically
  Adapts to text, images, or voice input

  📤 Auto-Publishing Pipeline
  Uploads to YouTube Shorts instantly
  AI-generated titles, descriptions, tags
  SEO-optimized for maximum reach

  🔄 Extend & Refine
  One-tap video extension (Veo only)
  Keep the vibe, extend the story
  No re-generation needed

  💳 Credit Management
  Real-time credit checking
  Prevents failed generations
  Session-based tracking with Redis

  🔔 Status Monitoring
  Real-time generation updates
  Webhook polling for long jobs
  Graceful error handling & cancellation

  🗂️ Session Storage
  Redis-powered state management
  Resume interrupted workflows
  Track generation history

  🎪 Perfect For

  | Creator Type | Use Case |
  |-------------|----------|
  | 🎥 Faceless Channels | Generate endless Shorts without showing face |
  | 🏢 Agencies | Scale content production 10x for clients |
  | 📱 Solo Creators | Daily Shorts from your phone, no laptop needed |
  | 🤖 AI Farms | Automate content pipelines end-to-end |
  | 🧪 Experimenters | Rapid prototyping of video ideas |
  | 📊 Marketers | A/B test video concepts at scale |

  🛠️ Tech Stack

  Telegram Bot API     →  User interface
  OpenAI GPT-4        →  Prompt generation
  KIE.ai              →  Video generation (Veo/Sora/Seedance)
  YouTube Data API    →  Auto-publishing
  Redis               →  Session & state management
  S3-compatible       →  Video storage
  n8n                 →  Orchestration layer

  Requirements:
  ✅ Telegram Bot Token
  ✅ OpenAI API Key
  ✅ KIE.ai Account (Veo/Sora/Seedance access)
  ✅ YouTube OAuth Credentials
  ✅ Redis Instance (recommended)
  ✅ S3-compatible Storage
  ✅ n8n Instance (cloud or self-hosted)

  🎬 Real-World Workflow Example

  You: 
  "A golden retriever puppy discovering snow for the first time"

  Bot: 
  ✨ Generating your video...
  📊 Credits: 50 remaining
  🎬 Using: Veo 3 Fast
  ⏱️ ETA: 2 minutes

  2 minutes later:
  ✅ Your video is ready!
  📺 Uploaded to YouTube Shorts
  🔗 Link: youtube.com/shorts/abc123
  👁️ Views: 0 → 1.2K (24 hours)

  [Extend Video] [Generate New]

  Result: Viral short created from your phone while waiting for coffee ☕

  🔧 Customization Ideas

  🎨 Extend the Platform
  Add TikTok publishing
  Include Instagram Reels
  Add Twitter video posts
  Support LinkedIn video

  🎙️ Alternative Inputs
  Replace Telegram with WhatsApp
  Add Discord bot interface
  Support Slack commands
  Email-to-video pipeline

  🎭 Creative Variations
  Swap OpenAI for Claude/Gemini
  Add custom style presets
  Include watermarking steps
  Generate captions automatically

  📊 Analytics & Tracking
  Log all generations to Google Sheets
  Track video performance metrics
  A/B test title/thumbnail combinations
  Monitor credit usage trends

  📊 Success Metrics

  After using this workflow for 30 days:

  | Metric | Before | After | Improvement |
  |--------|--------|-------|-------------|
  | ⏱️ Time per video | 45 min | 5 min | 9x faster |
  | 📹 Videos/week | 5 | 50+ | 10x volume |
  | 💰 Cost per video | $15 | $2 | 7.5x cheaper |
  | 📱 Creation location | Desktop only | Anywhere | ∞ flexibility |
  | 🧠 Prompt writing | Manual | Automated | No skill needed |

  🚀 Quick Start

  Import workflow to n8n
  Add credentials (Telegram, OpenAI, KIE.ai, YouTube, Redis)
  Configure video storage (S3)
  Activate workflow
  Message your bot and watch the magic happen

  Setup time: ~20 minutes  
  First video: ~5 minutes after setup

  🏷️ Tags

  telegram ai-video youtube-shorts automation content-creation openai veo sora seedance text-to-video social-media creator-tools faceless-channel redis s3 n8n-workflow telegram-bot video-automation shorts-generator

  📜 License

  MIT License - Use freely, modify, share, monetize!

  ⚡ Stop editing. Start generating. Scale your content empire. ⚡

  Created by Joe Venner | Built with ❤️ and n8n

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metadata_json:
  {"categories":["Marketing","Communication","Data Processing","AI/ML","DevOps"],"complexity":"medium","use_cases":["create viral short videos","share content on social media","automate video production","transform text into video","manage content in Telegram"],"estimated_setup_minutes":60,"required_services":["Telegram API","YouTube Data API","TikTok API","Instagram API","AWS S3","Redis"],"key_features":["AI-powered short video generation","Multi-platform video distribution","Telegram-based workflow execution","Text-to-video automation","Cross-service integration"],"target_audience":["content creators","social media managers","marketing teams"]}


name: Predict incidents and run autonomous remediation with GPT-4 and Slack
author_name: Cheng Siong Chin
author_username: cschin
categories: []
created_at: 2026-01-13T15:46:26.240Z
updated_at: 2026-01-13T15:46:26.240Z
url: https://n8n.io/workflows/12686
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  How It Works
  This workflow automates end-to-end customer journey management by intelligently routing queries through multiple AI models (OpenAI, Claude) based on complexity and context. Designed for customer success teams, support operations, and sales organizations, it solves the challenge of delivering personalized, context-aware responses at scale while maintaining conversation continuity. The system captures customer interactions, analyzes sentiment and intent, routes to appropriate AI models, generates tailored responses, and tracks engagement metrics. It integrates email automation, database logging, and multi-channel communication to create a seamless experience. By combining NVIDIA's specialized models for technical queries, OpenAI for general assistance, and Claude for complex reasoning, it ensures optimal response quality while reducing manual workload by 70%.

  Setup Steps
  Configure NVIDIA API credentials with appropriate model access 
  Add OpenAI API key with GPT-4 access for general query handling
  Set up Anthropic Claude API credentials for complex reasoning tasks
  Connect Gmail account for automated email sending and monitoring
  Configure Google Sheets with customer interaction tracking template
  Set webhook URL for external system integrations

  Prerequisites
  NVIDIA NIM API access, OpenAI API key, Anthropic API credentials 
  Use Cases
  Customer support automation with tiered response complexity 
  Customization
  Adjust AI model selection criteria based on query keywords or customer segments. 
  Benefits
  Reduces response time by 80% through instant AI-powered replies. 

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name: Route and reassign leads with SLA using Google Sheets and Slack
author_name: Muh Resky Adiansyah
author_username: adiardian
categories: []
created_at: 2026-01-14T05:11:07.902Z
updated_at: 2026-01-14T05:11:07.902Z
url: https://n8n.io/workflows/12702
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Lead-Routing-Engine-with-SLA-Auto-Reassignment

  This repository contains an SLA-based lead routing workflow built in n8n, designed to ensure fast lead response, fair sales distribution, and controlled escalation without relying on a full CRM system.

  The workflow focuses on routing discipline and operational safety, not feature completeness.

  What This Workflow Does

  At a high level, the system:
  1) Accepts new leads from a generic intake form
  2) Assigns leads to sales reps using round-robin
  3) Enforces a response SLA
  4) Automatically re-routes uncontacted leads
  5) Allows sales to mark leads as CONTACTED via Slack
  6) Escalates to a manager once if SLA is repeatedly violated

  Architecture Overview

  Core Components

  1) n8n 
  2) Google Sheets 
  3) Slack

  Primary Data Stores

  1) sales_sheet (list of active sales reps)
  2) lead_sheet (lead state and routing history)
  3) routing_state_sheet (global routing + escalation flags)

  End-to-End Flow

  A) Lead Intake & Normalization

  1) New leads enter via Form Trigger
  2) Phone numbers are normalized to 62xxxxxxxx (Indonesia International Direct Dialing code)
  3) A unique lead_id is generated
  4) Lead is initialized with:
     stage = NEW
     route_count = 0

  B) Initial Assignment (Round Robin)

  1) Active sales reps are loaded from sales_sheet
  2) Global last_index is read from routing_state_sheet
  3) Lead is assigned to the next sales rep in sequence
  4) Assignment metadata is stored:
      assigned sales
      timestamps
      route count
  5) last_index is updated centrally

  C) Slack Notification (New Lead)

  1) Assigned sales receives a Slack message
  2) Message includes a “Mark as CONTACTED” button
  3) SLA expectation is clearly communicated (1 hour by default)

  D) SLA Monitoring (Scheduled)

  1) A scheduled trigger runs every hour
  2) Workflow scans leads where:
     stage = NEW
     SLA window has elapsed since last assignment

  E) SLA Re-Routing

  For each qualifying lead:
  1) Lead is reassigned to the next sales rep
  2) Route count is incremented
  3) Timestamps are updated
  4) Slack notification is sent to the new assignee

  This process repeats until the lead is contacted or escalated.

  F) Controlled Escalation

  If route_count &gt;= threshold (default: 10):
  1) Workflow checks escalation state (escalated_&lt;lead_id&gt;)
  2) If not escalated yet:
     Manager is notified via Slack
     Escalation flag is written
  4) If already escalated:
     No further action is taken

  Escalation is one-time per lead.

  G) Stage Update via Slack (CONTACTED)

  1) Sales marks a lead as CONTACTED via Slack button
  2) Incoming Slack action is validated:
     Only assigned sales is allowed
     Only if current stage is NEW
  3) Update is idempotent
  4) Unauthorized or stale actions receive Slack feedback

  Once contacted:
  1) SLA routing stops
  2) Lead remains stable

  Safeguards Built In

  1) Ownership enforcement (Only the assigned sales rep can update a lead)
  2) Idempotent stage transitions (Prevents duplicate or stale Slack actions)
  3) One-time escalation (No notification spam)
  4) Fail-fast behavior (Missing sales data or malformed payloads halt execution early)

  Google Sheets Schema

  sales_sheet

  | Column   | Description     |
  |----------|-----------------|
  | name     | Sales name      |
  | email    | Optional        |
  | slack_id | Slack user ID   |
  | active   | ON / TRUE       |

  lead_sheet

  | Column         | Description           |
  | -------------- | --------------------- |
  | lead_id        | Unique identifier     |
  | name           | Lead name             |
  | phone          | Normalized phone      |
  | stage          | NEW / CONTACTED / QUALIFIED / CLOSED LOST       |
  | assigned_sales | Current owner         |
  | sales_slack_id | Slack ID              |
  | route_count    | Number of re-routes   |
  | created_at     | Creation timestamp    |
  | assigned_at    | Last assignment       |
  | last_routed_at | Last SLA routing      |
  | contacted_at   | When marked contacted |

  routing_state_sheet

  | key                 | value                  |
  | ------------------- | ---------------------- |
  | last_index          | Last round-robin index |
  | escalated_&lt;lead_id&gt; | Escalation timestamp   |

  Limitations (By Design)

  1) Google Sheets is not transactional
  2) SLA enforcement is time-bucketed, not real-time
  3) No concurrency locking across parallel runs
  4) Slack is required for interaction
  5) This is not a CRM, only a routing engine

  These constraints are explicit and intentional.

  When This Design Works Well

  1) Small to mid-size teams
  2) Human-response SLAs (minutes/hours)
  3) Teams needing discipline, not heavy tooling
  4) CRM-lite or pre-CRM environments

  When to Migrate

  Consider migrating if you need:

  1) High-volume ingestion
  2) Sub-minute SLA guarantees
  3) Strong transactional consistency
  4) Advanced analytics or forecasting

  The routing logic itself is portable to SQL or CRM systems.

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name: Enrich B2B leads for Attio CRM with Apollo, LinkedIn, news and GPT-4o
author_name: Blaine Holt
author_username: fenrirlabsnl
categories: []
created_at: 2026-01-14T12:47:48.189Z
updated_at: 2026-01-14T12:47:48.189Z
url: https://n8n.io/workflows/12710
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  B2B Lead Enrichment | Attio CRM

  This n8n template automates B2B lead research and enrichment for Attio CRM. It combines data from Apollo.io, LinkedIn scraping, and news sources with AI-powered analysis to generate actionable sales intelligence - turning hours of manual BDR research into minutes.

  Who is this for?

  Sales teams using Attio CRM who want to reduce time spent on lead research
  BDRs/SDRs who need rich prospect context before outreach
  Revenue operations teams looking to automate CRM enrichment at scale

  What problem does this workflow solve?

  Before reaching out to a prospect, sales reps typically spend 15-30 minutes researching company background, recent news, leadership team, and LinkedIn activity. This workflow automates that entire research process, freeing BDRs to focus on relationship building instead of data gathering.

  How it works

  Trigger: Manually execute (adapt to webhook or form trigger for automation)
  Apollo Enrichment: Fetches comprehensive company data by domain
  Parallel Processing: Three branches run simultaneously:
      News articles → Tavily extraction → AI summary
      LinkedIn company page → Scrape Creators → AI summary
      Leadership search (with web search) → Apollo person lookup → LinkedIn profiles → AI summary
  Validation: An LLM Critic agent verifies all claims using web search
  Final Output: Lead Enrichment Agent generates a structured dossier
  CRM Sync: Updates Attio company and people records

  Good to Know

  Estimated API Costs (per enrichment):
     Apollo.io: Varies by plan (credits-based)
     Scrape Creators: ~$0.01-0.05 per profile
     Tavily: ~$0.01 per extraction
     OpenAI GPT-4o: ~$0.10-0.30 depending on content length

  Rate Limits: Leadership profiles are processed sequentially to respect API limits. For bulk enrichment, consider adding delays between executions.

  Requirements

  Apollo.io account with API access
  Scrape Creators API key (for LinkedIn scraping)
  Tavily API key (for article extraction)
  OpenAI API key (GPT-4o model access)
  Attio CRM account with API access

  Setup

  Import the workflow into n8n
  Configure credentials for each service:
    	Apollo API (HTTP Header Auth with x-api-key)
    	Scrape Creators API
    	Tavily API
    	OpenAI API
    	Attio API
  Add these custom fields to your Attio Companies object:
    	positioning (text)
    	conversation_points (text)
    	leadership_conversations (text)
       enrichment_status (select with "complete" option)
  Test with a single domain before running at scale

  Customizing this workflow

     Trigger: Replace manual trigger with a webhook (real-time enrichment on new leads) or schedule node (batch processing)
     AI Prompts: Adjust the system prompts in AI agents to match your industry or ideal customer profile
     Output Fields: Modify the final Code node to map to your specific Attio field structure
     News Timeframe: Change the 6-month lookback in Apollo:LatestNews to your preferred range
     Leadership Depth: Adjust the number of leadership profiles to enrich based on your needs

  Made by www.fenrirlabs.nl

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