# templates

name: Estimate 4D/5D construction costs from Revit BIM models with DDC CWICR
author_name: Artem Boiko
author_username: datadrivenconstruction
categories: []
created_at: 2025-12-26T12:58:00.409Z
updated_at: 2025-12-26T12:58:00.409Z
url: https://n8n.io/workflows/12177
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  A professional BIM-to-cost pipeline that extracts data from Revit models (2015–2026), classifies elements with AI, decomposes them into construction works, and generates detailed cost estimates using the open-source DDC CWICR database. Produces HTML reports and Excel exports with full resource breakdown.

  Who's it for

  BIM Managers** automating quantity takeoff and cost estimation
  Cost Engineers** integrating 5D workflows into design pipelines
  Construction Companies** standardizing estimates from Revit models
  General Contractors** doing rapid budget checks during design
  MEP Engineers** pricing mechanical/electrical/plumbing systems
  Developers** building custom BIM-to-cost integrations

  What it does

  Extracts BIM data from Revit model via converter (RvtExporter)
  Classifies building vs non-building elements using AI
  Detects project type (Residential/Commercial/Industrial)
  Generates construction phases and assigns element types
  Decomposes each BIM type into detailed work items
  Searches DDC CWICR vector database for matching rates
  Calculates costs with unit mapping and resource breakdown
  Validates work completeness and checks for gaps
  Generates professional HTML report + Excel file

  How it works

  ┌─────────────────────────────────────────────────────────────────────────────┐
  │                          REVIT MODEL (.rvt)                                  │
  │                     Revit 2015–2026 supported                                │
  └─────────────────────────────────────────────────────────────────────────────┘
                                       ↓
  ┌─────────────────────────────────────────────────────────────────────────────┐
  │  BLOCK 1: CONVERSION                                                         │
  │  RvtExporter.exe → Excel with BIM element schedules                          │
  └─────────────────────────────────────────────────────────────────────────────┘
                                       ↓
  ┌─────────────────────────────────────────────────────────────────────────────┐
  │  BLOCK 2: DATA LOADING & CLASSIFICATION                                      │
  │  • Filter 3D View elements only                                              │
  │  • AI analyzes headers → aggregation rules (sum/mean/last)                   │
  │  • AI classifies building vs non-building elements                           │
  │  • Hard exclude: Grids, Levels, Annotations, Views, etc.                     │
  └─────────────────────────────────────────────────────────────────────────────┘
                                       ↓
  ┌─────────────────────────────────────────────────────────────────────────────┐
  │  BLOCK 3: PROJECT ANALYSIS (Stages 0–3)                                      │
  │  STAGE 0: Collect filtered BIM data                                          │
  │  STAGE 1: AI detects project type                                            │
  │  STAGE 2: AI generates construction phases                                   │
  │  STAGE 3: AI assigns element types to phases                                 │
  └─────────────────────────────────────────────────────────────────────────────┘
                                       ↓
  ┌─────────────────────────────────────────────────────────────────────────────┐
  │  BLOCK 4: WORK DECOMPOSITION (Stage 4)                                       │
  │  Loop through each BIM type:                                                 │
  │  • AI decomposes type into work items                                        │
  │  • Example: Window → Demolition, Installation, Sealing, Hardware             │
  │  • Prepares search queries for pricing                                       │
  └─────────────────────────────────────────────────────────────────────────────┘
                                       ↓
  ┌─────────────────────────────────────────────────────────────────────────────┐
  │  BLOCK 5: PRICING & CALCULATION (Stages 5–7)                                 │
  │  STAGE 5: Vector search in Qdrant (text-embedding-3-large, 3072 dim)         │
  │  STAGE 6: Map BIM units → Rate units (m² → 100 m²)                           │
  │  STAGE 7: Calculate costs (Qty × Unit Price)                                 │
  └─────────────────────────────────────────────────────────────────────────────┘
                                       ↓
  ┌─────────────────────────────────────────────────────────────────────────────┐
  │  BLOCK 6: VALIDATION & AGGREGATION                                           │
  │  STAGE 7.5: AI validates work completeness                                   │
  │  STAGE 8: Aggregate costs by phases                                          │
  └─────────────────────────────────────────────────────────────────────────────┘
                                       ↓
  ┌─────────────────────────────────────────────────────────────────────────────┐
  │  BLOCK 7: REPORT GENERATION (Stage 9)                                        │
  │  • Professional HTML report with expandable rows                             │
  │  • Excel-compatible XLS file                                                 │
  │  • Auto-opens in browser                                                     │
  └─────────────────────────────────────────────────────────────────────────────┘

  Pipeline Stages

  | Stage | Name | Description |
  |-------|------|-------------|
  | 0 | Collect | Gather filtered BIM data |
  | 1 | Project Type | AI detects Residential/Commercial/Industrial |
  | 2 | Phases | AI generates construction phases |
  | 3 | Assignment | AI assigns element types to phases |
  | 4 | Decomposition | AI breaks types into work items |
  | 5 | Vector Search | Query Qdrant for pricing rates |
  | 6 | Unit Mapping | Convert BIM units to rate units |
  | 7 | Calculation | Compute costs (Qty × Price) |
  | 7.5 | Validation | AI checks completeness, finds gaps |
  | 8 | Aggregation | Sum costs by phases |
  | 9 | Reports | Generate HTML + XLS outputs |

  Prerequisites

  | Component | Requirement |
  |-----------|-------------|
  | n8n | v1.30+ with Execute Command node |
  | Revit Exporter | RvtExporter.exe (provided separately) |
  | OpenAI API | For embeddings + LLM tasks |
  | Qdrant | Vector DB with DDC CWICR collections |
  | DDC CWICR Data | GitHub |
  | Windows | For Revit converter execution |

  Setup

  1. Configure File Paths

  In Setup - Define file paths node:
  {
    "path_to_converter": "C:\\path\\to\\RvtExporter.exe",
    "project_file": "C:\\path\\to\\your_project.rvt",
    "group_by": "Type Name",
    "language_code": "DE"
  }

  2. Select Language & Region

  | Code | Language | City | Currency |
  |------|----------|------|----------|
  | AR | Arabic | Dubai | AED |
  | ZH | Chinese | Shanghai | CNY |
  | DE | German | Berlin | EUR |
  | EN | English | Toronto | CAD |
  | ES | Spanish | Barcelona | EUR |
  | FR | French | Paris | EUR |
  | HI | Hindi | Mumbai | INR |
  | PT | Portuguese | São Paulo | BRL |
  | RU | Russian | St. Petersburg | RUB |

  3. Configure AI Model

  Connect your preferred LLM in the model nodes:

  | Provider | Model | Notes |
  |----------|-------|-------|
  | OpenAI | GPT-4o | Default, recommended |
  | Anthropic | Claude Opus 4 | High quality |
  | Google | Gemini 2.5 Pro | Good for large contexts |
  | xAI | Grok 4 | Fast inference |
  | DeepSeek | DeepSeek Chat | Cost-effective |
  | OpenRouter | Various | Multi-model access |

  4. Set Up Qdrant

  Ensure DDC CWICR collections are loaded:
  DE_BERLIN_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
  ENG_TORONTO_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
  RU_STPETERSBURG_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR
  ...

  5. Configure OpenAI Credentials

  Set up OpenAI API credential for:
  Embeddings (text-embedding-3-large, 3072 dimensions)
  LLM calls (if using OpenAI as primary model)

  Features

  | Feature | Description |
  |---------|-------------|
  | 🏗️ Revit Integration | Direct extraction from .rvt files (2015–2026) |
  | 🤖 Multi-LLM Support | OpenAI, Claude, Gemini, Grok, DeepSeek |
  | 🔍 Smart Classification | AI separates building from non-building elements |
  | 📊 Work Decomposition | Breaks BIM types into detailed work items |
  | 🎯 Vector Search | Semantic matching via Qdrant + OpenAI embeddings |
  | 🧮 Unit Mapping | Automatic conversion (m² → 100 m², pcs → sets) |
  | ✅ AI Validation | Checks for missing works and duplications |
  | 📈 Phase Aggregation | Costs grouped by construction phases |
  | 📄 HTML Report | Professional report with quality indicators |
  | 📑 Excel Export | XLS file with formulas and links |
  | 🌍 9 Languages | Full localization + regional pricing |

  Hard Exclude Categories

  The pipeline automatically excludes non-physical elements:

  Levels, Grids, Reference Planes
  Annotations, Dimensions, Text Notes
  Tags, Views, Sheets, Schedules
  Legends, Viewports, Section Boxes
  Scope Boxes, Match Lines
  Model Groups, Detail Groups
  Entourage (RPC people, cars, plants)

  Example Output

  Input: Residential building Revit model (45 element types)

  Processing:
  Project type detected: Residential Multi-Family
  Phases generated: Foundations → Structure → Envelope → MEP → Finishes
  Types assigned: 45 types → 5 phases
  Works decomposed: 45 types → 280 work items
  Rates found: 245/280 (87.5%)

  Output Files:
  project_2024-12-08.html  → Professional HTML report
  project_2024-12-08.xls   → Excel with full breakdown

  HTML Report Features:
  KPI summary (total cost, items, phases)
  Expandable phase sections
  Quality indicators (● green/yellow/red)
  Resource breakdown per work item
  Clickable rate codes
  Responsive design

  Output Structure

  📊 Cost Estimate: Residential Building
  ├── 📁 Phase 1: Foundations
  │   ├── Foundation walls — 125.5 m³ — €12,450
  │   ├── Concrete footings — 45.2 m³ — €8,340
  │   └── Waterproofing — 280 m² — €4,200
  ├── 📁 Phase 2: Structure
  │   ├── Concrete columns — 18 pcs — €9,720
  │   ├── Floor slabs — 450 m² — €67,500
  │   └── Stairs — 3 flights — €8,100
  ├── 📁 Phase 3: Envelope
  │   ├── Exterior walls — 680 m² — €95,200
  │   ├── Windows — 42 pcs — €25,200
  │   └── Roof system — 225 m² — €33,750
  └── 💰 TOTAL: €485,240

  Notes & Tips

  First run:** Conversion takes 1–3 minutes depending on model size
  Cached conversion:** Subsequent runs skip conversion if Excel exists
  Testing mode:** Limit to 10 types for faster debugging
  Rate accuracy:** Depends on DDC CWICR coverage for your region
  Custom phases:** AI adapts phases based on project type
  Missing rates:** Flagged with red indicator in report

  Extending the Pipeline

  Add custom rates:** Extend Qdrant collection with your pricing
  Chain to PM tools:** Connect to OpenProject, Monday, Asana
  Email reports:** Add email node after report generation
  Cloud storage:** Upload to Google Drive, OneDrive, S3
  Webhook trigger:** Replace manual trigger for API access

  Categories

  AI · Data Transformation · Document Ops · Files & Storage

  Tags

  bim, revit, cost-estimation, 5d-bim, 4d-bim, qdrant, vector-search, openai, construction, quantity-takeoff, html-report, multilingual

  Author

  DataDrivenConstruction.io  
  https://DataDrivenConstruction.io  
  info@datadrivenconstruction.io

  Consulting & Training

  We help AEC firms implement:
  BIM-to-cost automation pipelines
  4D/5D integration workflows
  Custom Revit data extractors
  AI-powered estimation systems
  Vector database deployment for construction data

  Contact us to adapt this pipeline to your Revit templates and regional pricing.

  Resources

  DDC CWICR Database:** GitHub
  Qdrant Documentation:** qdrant.tech/documentation
  OpenAI Embeddings:** platform.openai.com
  n8n Execute Command:** docs.n8n.io

  ⭐ Star us on GitHub! github.com/datadrivenconstruction/DDC-CWICR

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name: E-commerce product mockups from images with OpenAI DALL-E, remove.bg and G-Drive
author_name: SpaGreen Creative
author_username: spagreen
categories: []
created_at: 2025-12-27T03:44:04.355Z
updated_at: 2025-12-27T03:44:04.355Z
url: https://n8n.io/workflows/12193
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 automatically generates professional e-commerce product mockups from product images. The workflow is perfect for e-commerce store owners, product marketers, and content creators who need to create consistent, high-quality product visuals for their online stores, social media, and marketing materials.

  Features
  Dual Input Methods**: Accepts product images via file upload or URL
  Background Removal**: Automatically removes backgrounds from product images using remove.bg API
  AI-Powered Mockups**: Generates premium e-commerce mockups using OpenAI's DALL-E
  Professional Prompts**: Uses detailed design prompts for luxury e-commerce aesthetics
  Google Drive Integration**: Automatically saves both PNG files and final mockups to Google Drive

  How It Works
  The workflow starts with a form submission where users provide:
     Product image (file upload or URL)
     Product name/title
  System detects whether the image is a file or a URL.
  For uploaded files:
     Processed through remove.bg to remove the background
     Transparent PNG is uploaded to Google Drive
     OpenAI generates a professional mockup based on product image
     Final mockup uploaded on Drive & notify user
  For URL inputs:
     Image downloaded from the URL
     Background removal and mockup generation process is applied
     Results are delivered back to the user

  Requirements
  remove.bg API credentials** for background removal
  OpenAI API credentials** for DALL-E image generation
  Google Drive OAuth2 credentials** for file storage

  Important Notes
  Image Processing**: All images are processed with professional-grade background removal
  AI Prompting**: The workflow uses detailed prompts designed for luxury e-commerce aesthetics
  File Storage**: Both PNG files and final mockups are stored in a designated Google Drive folder
  Conditional Logic**: The workflow intelligently routes based on input type (file vs. URL)
  Error Handling**: Includes retry logic for AI image generation

  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: Monitor hotel competitor rates and answer WhatsApp Q&A using OpenAI GPT-4.1
author_name: Lee Lin
author_username: l2l
categories: []
created_at: 2025-12-29T02:58:58.642Z
updated_at: 2025-12-29T02:58:58.642Z
url: https://n8n.io/workflows/12246
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  How It Works
  Top Branch Workflow A*

  1. The Market Intelligence: 
  Patrols the Market:** Runs hourly to scrape competitor rates for future days.
  Gathers Intel:** If prices spike, it instantly checks event announcements to see if a major event is driving demand.
  Crunches Numbers:** Calculates the exact price gap and filters out noise.

  2. The Revenue Manager: 
  Sets Strategy:** The AI Agent reviews the price gaps, competitor moves, and event signals.
  Reports:** Writes a strategic Executive Summary and sends it to your WhatsApp.


  Bottom Branch Workflow B*

  3. The Consultant: 
   Recall: When you ask a question via WhatsApp, the bot retrieves the saved analysis, historical rates, and event schedule.
    Answer: It acts as an on-demand analyst, conducting further analysis to give an informed answer to questions

  Setup Steps
  1. Config: Add your hotel + competitor hotels (IDs/names) in the Config node.

  2. Monitor Window: Set how far ahead you want to monitor (e.g., daysAhead = 30) in the Config node.

  3. Sensitivity: Set how sensitive alerts should be (e.g., alert only if competitor moves &gt; 10%) in the Significant Competitor Change node.

  4. Connect Credentials:

  Amadeus (to fetch hotel prices)
  WhatsApp (to send alerts)
  Postgres/SQL (to store price snapshots, history, summary)
  OpenAI (for the AI Agents)

  5. Event Source: Update the Fetch VCC nodes to scrape your local convention center or event site.

  6. Run a test:

  Trigger Workflow A manually and confirm you receive a WhatsApp alert.

  Reply to that WhatsApp message to test Workflow B (Q&A).

  Use Cases & Benefits
  For Revenue Managers: Automate the "rate shop" routine and catch competitor moves without opening a spreadsheet.

  For Sales & Marketing Teams: Go beyond raw data. Pairing "what changed" with "why changed" instantly.

  For Hotel Leadership: Perfect for GMs and division leaders who need instant, decision-ready alerts via WhatsApp.

  ⚡ Zero-Touch Efficiency: Eliminates hours of manual searching by automating rate checks 3x daily. 
  🧠 Contextual Intelligence: Tracks price AND explains why it moved by cross-referencing local events. 
  🤖 Actionable Strategy: AI doesn't just report numbers; it recommends specific pricing tactics. 
  📉 Long-Term Vision: Builds a permanent database of rate history, enabling the AI to answer complex trend questions over time.

  📬 Want to Customize This?
  leelin.business@gmail.com

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name: Generate text, image, and video-to-video clips with WAN 2.6 via KIE.AI
author_name: Muhammad Farooq Iqbal
author_username: mfarooqone
categories: []
created_at: 2025-12-29T06:57:12.581Z
updated_at: 2025-12-29T06:57:12.581Z
url: https://n8n.io/workflows/12253
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n template provides a comprehensive suite of WAN 2.6 video generation capabilities through the KIE.AI API. The workflow includes three independent video generation workflows: text-to-video, image-to-video, and video-to-video. Each workflow can be used independently to create videos from different input types, making it perfect for content creators, marketers, and video production teams.

  Use cases are many: Create videos from text descriptions without any input media, transform static images into animated videos, enhance existing videos with new styles and effects, generate engaging video content for social media, automate video production workflows, create video variations from the same source, produce marketing videos at scale, repurpose content across different video formats, or streamline video creation pipelines for content teams!

  Good to know

  The workflow includes three independent WAN 2.6 video generation capabilities via KIE.AI API:
    Text-to-Video: Creates videos directly from text prompts without requiring input images or videos
    Image-to-Video: Transforms static images into animated videos based on text prompts
    Video-to-Video: Enhances or transforms existing videos with new styles and effects
  Each workflow can be used independently based on your input type and needs
  Supports two resolution options: 720p or 1080p
  Supports three duration options: 5, 10, or 15 seconds
  Text-to-video creates videos purely from text descriptions - no media input required
  Image-to-video animates static images with customizable prompts for style and movement
  Video-to-video allows you to transform existing videos with new visual styles and effects
  KIE.AI pricing: Check current rates at https://kie.ai/ for video generation costs
  Processing time: Varies based on video length and KIE.AI queue, typically 1-5 minutes for generation
  Media requirements: Image and video files must be publicly accessible via URL (HTTPS recommended)
  Supported image formats: PNG, JPG, JPEG, WEBP
  Supported video formats: MP4, MOV, AVI, WEBM
  Automatic polling system handles processing status checks and retries for all workflows

  How it works

  The template includes three independent workflows that can be used separately based on your input type:

  1. Text-to-Video (Top Section):
  Video Parameters Setup: Set prompt, duration (5, 10, or 15 seconds), and resolution (720p or 1080p) in 'Set Video Parameters' node
  Video Generation Submission: Parameters are submitted to KIE.AI API using WAN 2.6 text-to-video model
  Processing Wait: Workflow waits 5 seconds, then polls the generation status
  Status Check: Checks if video generation is complete, queuing, generating, or failed
  Polling Loop: If still processing, workflow waits and checks again until completion
  Video URL Extraction: Once complete, extracts the generated video file URL from the API response
  Video Download: Downloads the generated video file for local use

  2. Image-to-Video (Middle Section):
  Video Parameters Setup: Set prompt, image URL, duration, and resolution in 'Set Prompt & Image Url' node
  Video Generation Submission: Parameters are submitted to KIE.AI API using WAN 2.6 image-to-video model
  Processing Wait: Workflow waits 5 seconds, then polls the generation status
  Status Check: Checks if video generation is complete, queuing, generating, or failed
  Polling Loop: If still processing, workflow waits and checks again until completion
  Video URL Extraction: Once complete, extracts the generated video file URL from the API response
  Video Download: Downloads the generated video file for local use

  3. Video-to-Video (Bottom Section):
  Video Parameters Setup: Set prompt, video URL, duration, and resolution in 'Set Video URL and Prompt' node
  Video Generation Submission: Parameters are submitted to KIE.AI API using WAN 2.6 video-to-video model
  Processing Wait: Workflow waits 5 seconds, then polls the generation status
  Status Check: Checks if video generation is complete, queuing, generating, or failed
  Polling Loop: If still processing, workflow waits and checks again until completion
  Video URL Extraction: Once complete, extracts the generated video file URL from the API response
  Video Download: Downloads the generated video file for local use

  All workflows automatically handle different processing states (queuing, generating, success, fail) and retry polling until video generation is complete. Each workflow operates independently, allowing you to use only the video generation type you need.

  How to use

  Setup Credentials: 
     Configure KIE.AI API key as HTTP Bearer Auth credential (used for all three workflows)
  Choose Your Workflow:
     For Text-to-Video: Update 'Set Video Parameters' node with prompt, duration (5/10/15), and resolution (720p/1080p)
     For Image-to-Video: Update 'Set Prompt & Image Url' node with prompt, image URL (publicly accessible), duration, and resolution
     For Video-to-Video: Update 'Set Video URL and Prompt' node with prompt, video URL (publicly accessible), duration, and resolution
  Set Video Parameters: 
     prompt: Detailed text description of the desired video content, style, and effects
     duration: 5, 10, or 15 seconds (only these values supported)
     resolution: 720p or 1080p (only these values supported)
     image_url/video_urls: Publicly accessible URL for image-to-video or video-to-video workflows
  Deploy Workflow: Import the template and activate the workflow
  Trigger Generation: Use manual trigger to test, or replace with webhook/other trigger
  Receive Video: Get generated video file URL and download the video file

  Pro tip: Write detailed, descriptive prompts to guide the video generation - the more specific your prompt, the better the video output. Include scene details, camera movements, lighting, style, and visual effects in your prompt. For image-to-video and video-to-video, ensure your input media is hosted on public URLs (HTTPS recommended). The workflows automatically handle polling, status checks, and video download, so you can set it and forget it. You can use different workflows for different use cases - text-to-video for pure creation, image-to-video for animating static content, and video-to-video for enhancing existing videos.

  Requirements

  KIE.AI API** account for accessing WAN 2.6 video generation models
  Text Prompt** describing the desired video content (required for all workflows)
  Image File URL** (for image-to-video) that is publicly accessible (HTTPS recommended)
  Video File URL** (for video-to-video) that is publicly accessible (HTTPS recommended)
  Duration** value: 5, 10, or 15 seconds only
  Resolution** value: 720p or 1080p only
  n8n** instance (cloud or self-hosted)
  Supported image formats: PNG, JPG, JPEG, WEBP
  Supported video formats: MP4, MOV, AVI, WEBM

  Customizing this workflow

  Workflow Selection: Use only the workflows you need by removing or disabling nodes for text-to-video, image-to-video, or video-to-video. Each workflow operates independently.

  Trigger Options: Replace the manual trigger with webhook trigger for API-based video generation requests, schedule trigger for batch processing, or form trigger for user submissions.

  Video Settings: Modify duration (5, 10, or 15 seconds) and resolution (720p or 1080p) in the respective 'Set' nodes to match your content needs. Note: Only these specific values are supported.

  Prompt Engineering: Enhance prompts in the 'Set' nodes with detailed scene descriptions, visual effects, camera movements, style effects, and artistic directions for better video quality. The more descriptive your prompt, the better the output.

  Workflow Chaining: Connect workflows together - generate a video with text-to-video, then enhance it with video-to-video, or create an image-to-video, then transform it further.

  Batch Processing: Add loops to process multiple prompts, images, or videos from a list or spreadsheet automatically, generating videos in batch.

  Storage Integration: Add nodes to save generated videos to Google Drive, Dropbox, S3, or other storage services before or after download.

  Post-Processing: Add nodes between video generation and download to add captions, apply filters, add watermarks, or integrate with video editing tools.

  Error Handling: Add notification nodes (Email, Slack, Telegram) to alert when video generation completes, fails, or encounters errors.

  Content Management: Add nodes to log video generation results, track processing status, or store outputs in databases or spreadsheets.

  Video Variations: Create multiple video variations with different prompts and settings for A/B testing or content variations.

  Social Media Integration: Add nodes after video download to automatically upload videos to YouTube, Instagram, TikTok, or other platforms.

  Quality Control: Add conditional logic to check video quality, file size, or other characteristics before proceeding with download or distribution.

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name: Send sales forecast charts and answer Q&A on WhatsApp with OpenAI
author_name: Lee Lin
author_username: l2l
categories: []
created_at: 2025-12-30T00:48:35.685Z
updated_at: 2025-12-30T00:48:35.685Z
url: https://n8n.io/workflows/12289
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  How It Works 
  Top Branch Workflow*

  1. The Data Scientist: 
     Ingest: Pulls historical sales data from Google Sheets.
     Math Engine: Runs 7 statistical algorithms (e.g., Seasonal Naive, Linear Trend, Regression). It backtests them against your history and scientifically selects the winner with the lowest error rate.


  2. The Data Analyst: 
     Interpret: The AI Agent takes the mathematical output and translates it into business insights, assigning confidence scores based on error margins.
     Report: Generates a visual trend chart (PNG) and sends a complete briefing to your phone.


  Bottom Branch Workflow*

  3. The Consultant: AI Agent 2 handles the follow-up questions. It pulls the latest analysis context and checks historical rate data to give an informed answer.
     Recall: When you ask a question via WhatsApp, the bot retrieves the saved forecast state.
     Answer: It acts as an on-demand analyst, comparing current forecasts against historical actuals to give you instant answers.

  Setup Steps
  1) Google Sheet: Prepare columns: Year, Month, Sales. Map the Sheet ID in the "Workflow Configuration" node.
  2) Forecast Engine: No config needed. It automatically detects seasonality vs. linear trends.
  3) Database: Create a table latest_forecast to store the JSON output.
  4) Credentials: Connect Google Sheets, OpenAI, and WhatsApp

  Use Cases & Benefits
  For Business Owners: 
  Gain enterprise-grade forecasting on autopilot. Always have a sophisticated financial outlook running in the background 24/7.

  For Sales Leaders: 
  Get immediate visibility into future revenue trends. Bypass the wait for end-of-month manual reports and get a strategic "pulse check" delivered instantly to your phone.


  🤖Virtual Data Team: Instantly add the capabilities of a Data Scientist and Data Analyst to your business or division. It works alongside your existing team to handle the heavy lifting, or stands in as your dedicated automated department.

  🧠Precision & Trust: Combines the best of both worlds: rigorous, deterministic code for the math (no hallucinations) and advanced AI for the strategic explanation. You get numbers you can trust with context you can use.

  ⚡Decision-Ready Insights: Stop digging through dashboards. High-level intelligence is pushed directly to you on WhatsApp, allowing you to make faster, data-driven decisions from anywhere.

  📬 Want to Customize This?
  leelin.business@gmail.com

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name: Manage your Shopify store via AI assistant with OpenAI and MCP server
author_name: SpaGreen Creative
author_username: spagreen
categories: []
created_at: 2025-12-30T06:39:45.547Z
updated_at: 2025-12-30T06:39:45.547Z
url: https://n8n.io/workflows/12296
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 Shopify 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, and provide store analytics through natural language commands.

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

  Requirements
  Shopify Access Token**: For accessing Shopify 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
  Shopify Access Token**: Configure with proper permissions for your store
  OpenAI API**: Set up with appropriate model access (gpt-4.1-mini or similar)
  Notification Services**: Configure each service with proper API keys and target IDs

  Important Notes
  MCP Server Setup**: The workflow includes a Shopify MCP Server that must be properly configured for production use
  Tool Selection**: The MCP Client includes specific Shopify 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 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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metadata_json:
  {"categories":["E-commerce","AI/ML"],"complexity":"medium","use_cases":["automate store operations","process orders via natural language","generate store analytics","manage products with chat interface"],"estimated_setup_minutes":30,"required_services":["Shopify","OpenAI","Discord","Telegram"],"key_features":["MCP integration for AI context","Natural language product management","Order processing automation","Real-time store analytics"],"target_audience":["Shopify store owners","E-commerce managers","AI integrators"]}


author_name: Sridevi Edupuganti
author_username: edupuganti
categories: []
created_at: 2025-12-30T09:39:58.256Z
updated_at: 2025-12-30T09:39:58.256Z
url: https://n8n.io/workflows/12299
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:22
name:
  Generate 5-level AI explanations for different audiences from Telegram to Google Docs with GPT-4.1-mini

description:
  Description

  Ask any question and get five different answers instantly. Each answer is written for a different audience—from kids to business executives. Your Telegram bot delivers all five explanations in under 10 seconds and saves them to Google Docs automatically. Perfect for teachers, writers, and anyone who needs to explain things to different people.

  Who's It For

  • Educators creating multi-grade  
  curriculum content
  •	Content creators generating material for diverse audiences
  •	Technical writers producing documentation at different expertise levels
  •	Parents explaining complex topics to children
  •	Anyone who needs to explain things to different people.

  How It Works

  •	Transforms any question into five distinct explanations: kid-friendly stories (5-year-olds), relatable content (teenagers), professional explanations (graduates), academic analysis (PhD researchers), and strategic insights (business executives)
  •	Five AI agents process simultaneously for 3-8 second response times
  •	Delivers six formatted Telegram messages (header + five explanations)
  •	Automatically archives complete conversations to Google Docs
  •	Uses binary tree merge architecture for reliable data handling

  How to Set Up

  •	Create Telegram bot via @BotFather and add token to n8n credentials
  •	Obtain OpenAI API key and add to n8n credentials
  •	Connect Google account to grant Docs access
  •	Create blank Google Doc and paste URL in workflow's Google Docs node
  •	Activate workflow and test with any question

  Requirements

  •	Telegram Bot API token (free)
  •	OpenAI API key (pay-per-use
  •	Google account with Docs access (free)
  •	n8n instance (cloud or self-hosted)

  How to Customize
  •	Modify AI prompts in 'Create 5 Items' node for different tones and styles
  •	Adjust character limits in formatting nodes to control message length
  •	Change output destinations from Telegram to Slack, email, or other platforms
  •	Switch AI providers from OpenAI to alternatives
  •	Add additional comprehension levels by duplicating AI agent nodes

  Need Help?

  For detailed notes and implementation, please leverage the README document at:
  https://drive.google.com/file/d/19Fx-FoihL70qpOi4CnEwQ6Sud2dbUnE_/view?usp=sharing

  Join the Discord (https://discord.com/invite/XPKeKXeB7d) or
  Join the n8n community forum (https://community.n8n.io/) for support

nodes_used:
  ["n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.lmChatOpenAi","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.telegramTrigger","n8n-nodes-base.set","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","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.merge","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.googleDocs","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":["AI/ML","Education","Communication"],"complexity":"medium","use_cases":["generate audience-specific content","explain concepts for different levels","automate document creation"],"estimated_setup_minutes":5,"required_services":["Telegram","Google Docs"],"key_features":["GPT-4.mini integration","audience-aware content generation","automatic document synchronization"],"target_audience":["educators","content creators","admin"]}


name: Find high-quality remote jobs with OpenAI, Decodo, and Google Sheets
author_name: Kevin Meneses
author_username: pythonia-kevin
categories: []
created_at: 2025-12-30T15:39:03.823Z
updated_at: 2025-12-30T15:39:03.823Z
url: https://n8n.io/workflows/12304
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  What this workflow does

  This workflow automates the discovery, evaluation, and notification of job opportunities based on a candidate’s professional profile.

  It fetches remote job listings, compares each role against a structured candidate profile stored in Google Sheets, and uses AI to evaluate real alignment in terms of skills, seniority, salary, industry, and role complexity.

  Only the most relevant opportunities are kept, stored in Google Sheets, and delivered via email as a Top 5 shortlist.

  Decodo – Web Scraper for n8n

  How to configure (quick setup)

  Define the candidate profile in Google Sheets (skills, salary expectations, preferences).


  Configure credentials (Google Sheets, Gmail, decodo, AI provider).

  Set the matching threshold (e.g. skill match ≥ 90%).

  Run the workflow manually or on a schedule.

  Output

  Structured job match results in Google Sheets

  Automated email with the Top 5 best-matched job opportunities

nodes_used:
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metadata_json:
  {"categories":["Recruiting","Career Development","Data Processing"],"complexity":"medium","use_cases":["Automate job discovery","AI-powered job matching","Personalized job alerts","Remote job filtering","Profile alignment scoring"],"estimated_setup_minutes":45,"required_services":["Google Sheets","OpenAI","Decodo","Email Service"],"key_features":["Semantic job matching","Smart priority ranking","Automated email notifications","Dynamic profile comparison","Remote job filtering"],"target_audience":["Job seekers","Career coaches","Recruiters"]}


name: Create & track LinkedIn posts with Google Sheets, GPT-5.1, Unsplash, and Sona
author_name: Sona Labs
author_username: sona
categories: []
created_at: 2025-12-30T23:00:52.691Z
updated_at: 2025-12-30T23:00:52.691Z
url: https://n8n.io/workflows/12325
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automate LinkedIn content creation by managing ideas in Google Sheets, generating professional AI-written posts, intelligently selecting relevant Unsplash images, sending drafts for email approval, and publishing directly to LinkedIn.

  How it works

  Step 1: Scheduled Sheet Check
  Workflow runs daily at midnight (customizable to hourly/weekly)
  Fetches posts from Google Sheet marked with Status = "Ready"
  Processes one post per run, updates status to "In Progress"

  Step 2: AI Content Generation
  GPT-5.1 creates engaging LinkedIn post based on your inputs
  Generates content with proper hashtags, formatting, and tone
  Follows your specified content type (tip, story, announcement, etc.)

  Step 3: Quality Validation
  Automatically checks character limits (3000 max)
  Validates minimum hashtag requirements (3+)
  Loops back to regenerate if quality checks fail

  Step 4: Email Approval Workflow
  Formats post as HTML email with professional styling
  Sends preview to your Gmail for review
  Waits for your approval response before proceeding
  Nothing posts without explicit confirmation

  Step 5: Smart Image Handling
  If you provided image URL: Downloads from Google Drive, Dropbox, or direct links
  If no URL is provided: Fetch 10 images from Unsplash and use AI to select the best one.
  If "Include Image?" is "No": Posts text-only content
  Automatically converts share links to downloadable formats

  Step 6: LinkedIn Publishing & Tracking
  Posts approved content directly to your LinkedIn profile
  Uses appropriate API endpoint based on whether image is included
  Updates Google Sheet status to "Posted" for successful posts
  Marks "Rejected" posts in sheet for review and editing

  What you'll get

  Batch content planning**: Queue multiple posts in advance via Google Sheets
  Consistent posting schedule**: Automated daily publishing without manual work
  Professional AI content**: GPT-5.1 generates engaging, platform-optimized posts
  Full approval control**: Review every post before it goes live
  Flexible image options**: Your images, AI-generated, or text-only
  Quality assurance**: Built-in checks prevent poorly formatted posts
  Status tracking**: Monitor what's ready, in progress, rejected, or posted
  Smart link conversion**: Automatically handles Google Drive and Dropbox share links

  Requirements

  Accounts & credentials:
  OpenAI API key (requires paid plan for GPT-5.1)
  Gmail account (for approval workflow)
  Google account (for Sheets integration)
  LinkedIn account (for publishing)
  Unsplash API key (for getting images)

  Google Sheet setup:
  Create a sheet with these columns:
  Topic/Subject (required) - Main idea for the post
  Content Type (required) - e.g., "Tip", "Story", "Announcement"
  Tone (required) - e.g., "Professional", "Casual", "Inspirational"
  Target Audience (optional) - Who you're writing for
  Additional Notes (optional) - Specific points to include
  Image link for your post (optional) - URL to your image
  Include Image? (required) - "Yes" or "No"
  Status (required) - "Ready" to trigger workflow

  Setup steps

  Import workflow - Click "Use workflow" to add to your n8n instance

  Connect credentials:
     Google Sheets: Authenticate and select your sheet from dropdown
     OpenAI: Add your API key in both AI nodes
     Gmail: Authenticate and update recipient email in approval node
     LinkedIn: Authenticate (your profile auto-populates)

  Create your content sheet - Add the required columns and fill with post ideas

  Test the workflow:
     Add one test row with Status = "Ready"
     Run workflow manually
     Check email for approval
     Verify post appears on LinkedIn

  Configure schedule - Default is daily at midnight; adjust Schedule Trigger node for different frequency

  Start batching - Add multiple ideas to your sheet and let automation handle the rest

  Tips for best results

  Be specific in Topic/Subject: "5 ways to improve team productivity" beats "productivity tips"
  Mix content types and tones to keep your feed engaging
  Use Additional Notes for data points, statistics, or specific examples. You can also include links that the AI can use for the posts.
  Start with text-only posts to validate content quality before adding images
  Review rejected posts carefully and refine your inputs
  Batch 10-20 ideas at once for weeks of automated content

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metadata_json:
  {"categories":["Marketing","Content Creation","Social Media Management"],"complexity":"medium","use_cases":["Automate social media content","Generate LinkedIn posts with AI","Synchronize ideas with Google Sheets"],"estimated_setup_minutes":30,"required_services":["Google Sheets","Unsplash","OpenAI","LinkedIn API","n8n GPT Copy"],"key_features":["Scheduled sheet reading","AI content generation","Image selection from Unsplash","Email approval workflow","Direct LinkedIn publishing"],"target_audience":["Social Media Managers","Content Creators","Marketing Teams"]}


name: Scrape physician profiles from BrowserAct into Google Sheets and notify Slack
author_name: Madame AI Team | Kai
author_username: madame-ai
categories: []
created_at: 2026-01-01T06:03:29.887Z
updated_at: 2026-01-01T06:03:29.887Z
url: https://n8n.io/workflows/12345
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:21
description:
  Scrape physician profiles from BrowserAct to Google Sheets

  This workflow automates the process of building a targeted database of healthcare providers by scraping physician details for a specific location and syncing them to your records. It leverages BrowserAct to extract data from healthcare directories and ensures your database stays clean by preventing duplicate entries.

  Target Audience
  Medical recruiters, pharmaceutical sales representatives, lead generation specialists, and healthcare data analysts.

  How it works
  Define Location: The workflow starts by setting the target Location and State in a Set node.
  Scrape Data: A BrowserAct node executes a task (using the "Physician Profile Enricher" template) to search a healthcare directory (e.g., Healow) for doctors matching the criteria.
  Parse JSON: A Code node takes the raw string output from the scraper and parses it into individual JSON objects.
  Update Database: The workflow uses a Google Sheets node to append new records or update existing ones based on the physician's name, preventing duplicates.
  Notify Team: A Slack node sends a message to a specific channel to confirm the batch job has finished successfully.

  How to set up
  Configure Credentials: Connect your BrowserAct, Google Sheets, and Slack accounts in n8n.
  Prepare BrowserAct: Ensure the Physician Profile Enricher template is saved in your BrowserAct account.
  Setup Google Sheet: Create a new Google Sheet with the required headers (listed below).
  Select Spreadsheet: Open the Google Sheets node and select your newly created file and sheet.
  Set Variables: Open the Define Location node and input your target Location (City) and State.
  Configure Notification: Open the Slack node and select the channel where you want to receive alerts.

  Google Sheet Headers
  To use this workflow, create a Google Sheet with the following headers:
  Name
  Specialty
  Address

  Requirements
  BrowserAct* account with the *Physician Profile Enricher** template.
  Google Sheets** account.
  Slack** account.

  How to customize the workflow
  Change the Data Source: Modify the BrowserAct template to scrape a different directory (e.g., Zocdoc or WebMD) and update the Google Sheet columns accordingly.
  Switch Notifications: Replace the Slack node with a Microsoft Teams, Discord, or Email node to suit your team's communication preferences.
  Enrich Data: Add an AI Agent node after the Code node to format addresses or research the specific clinics listed.

  Need Help?
  How to Find Your BrowserAct API Key & Workflow ID
  How to Connect n8n to BrowserAct
  How to Use & Customize BrowserAct Templates

  Workflow Guidance and Showcase Video

  Automate Medical Lead Gen: Scrape Healow to Google Sheets & Slack

nodes_used:
  ["n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.slack","n8n-nodes-browseract.browserAct","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Data Processing","Healthcare"],"complexity":"medium","use_cases":["Extract physician data","Build provider database","Prevent duplicates","Sync to spreadsheets","Get Slack alerts"],"estimated_setup_minutes":5,"required_services":["Google Sheets (Google Drive or Google Apps Script)","Slack","BrowserAct"],"key_features":["Web scraping from healthcare directories","Data deduplication logic","Multi-channel notification system"],"target_audience":["Medical recruiters","Sales representatives","Lead generation managers"]}


name: Auto-reply to Telegram messages using BrowserAct and Google Gemini
author_name: Madame AI Team | Kai
author_username: madame-ai
categories: []
created_at: 2026-01-01T06:56:42.915Z
updated_at: 2026-01-01T06:56:42.915Z
url: https://n8n.io/workflows/12359
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Auto-reply to Telegram messages using BrowserAct & Google Gemini

  This workflow acts as a smart, 24/7 personal assistant for your Telegram chats. It runs on a schedule to monitor your message history, uses AI to decide if a reply is necessary, drafts a personalized response, and sends it back to the user, all while handling delivery verification and potential CAPTCHA challenges via BrowserAct.

  Target Audience
  Community managers, busy professionals, and customer support teams who need to manage Telegram communications efficiently.

  How it works
  Scheduled Check: Every 15 minutes, the workflow triggers BrowserAct to fetch the latest chat history.
  Analysis: An AI Agent (using Google Gemini) reviews the conversation. It determines if the last message requires a response (e.g., a question) or if the chat is idle.
  Drafting: If a reply is needed, the AI drafts a personalized message that includes the user's name and a standard footer disclaimer.
  Formatting: A Code node cleans up the text to ensure proper line breaks and formatting for Telegram.
  Delivery: BrowserAct executes the task to send the drafted reply. The workflow loops to check the task status, ensuring the message is delivered successfully.

  How to set up
  Configure Credentials: Connect your BrowserAct and Google Gemini accounts in n8n.
  Prepare BrowserAct: Ensure the Telegram Personal Assistant template is saved in your BrowserAct account.
  Set Schedule: The default trigger interval is 15 minutes. Adjust the Schedule Trigger node if you need a different frequency.
  Activate: Turn on the workflow to start monitoring your chats.

  Requirements
  BrowserAct* account with the *Telegram Personal Assistant** template.
  Google Gemini** account.
  Telegram** account (accessed via BrowserAct).

  How to customize the workflow
  Change AI Persona: Modify the system prompt in the Chatting & Answering AI agent to change the tone from "Professional Support" to "Casual Assistant" or "Sales Representative."
  Adjust Frequency: Change the Schedule Trigger interval to run every 5 minutes for faster responses or hourly for less urgency.
  Add Notification: Add a Slack or Email node after the delivery step to get notified whenever the bot sends a reply.

  Need Help?
  How to Find Your BrowserAct API Key & Workflow ID
  How to Connect n8n to BrowserAct
  How to Use & Customize BrowserAct Templates

  Workflow Guidance and Showcase Video

  Telegram Personal Assistant: Auto-Read Chats & Auto-Reply them with n8n

nodes_used:
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metadata_json:
  {"categories":["Communication","AI/ML","Automation"],"complexity":"medium","use_cases":["Auto-reply to chats","Monitor message history","Draft personalized responses","Handle verification challenges"],"estimated_setup_minutes":15,"required_services":["Telegram","BrowserAct","Google Gemini"],"key_features":["Scheduled message monitoring","AI-powered reply selection","CAPTCHA handling","Personalized response drafting","Delivery verification"],"target_audience":["Community managers","Customer support teams","Busy professionals"]}


name: Create WooCommerce products and WordPress posts from product links via Telegram and BrowserAct
author_name: Madame AI Team | Kai
author_username: madame-ai
categories: []
created_at: 2026-01-01T06:58:33.834Z
updated_at: 2026-01-01T06:58:33.834Z
url: https://n8n.io/workflows/12360
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Automate product creation from links to WordPress & WooCommerce using Telegram & BrowserAct

  This workflow is a powerful e-commerce assistant that takes a raw product link (from any online store) and automatically creates optimized listings for your own platforms. It uses AI to write persuasive sales copy and blog articles, generates SEO-friendly image metadata, and syncs everything directly to WooCommerce and WordPress.

  Target Audience
  Dropshippers, affiliate marketers, and e-commerce store owners who want to scale their product catalog and content marketing effortlessly.

  How it works
  Analyze Intent: The workflow receives a message via Telegram. An AI Agent classifies it to see if it's a product link or a casual chat.
  Scrape Details: If a link is detected, BrowserAct executes a background task to scrape the product's title, price, description, images, and reviews.
  AI Strategy: A "Senior Copywriter" AI (using OpenAI/Gemini) processes the raw data. It writes a high-converting WooCommerce description (with HTML formatting), drafts an engaging blog post review, and generates SEO filenames/alt-text for all images.
  Sync to Store:
      WooCommerce: Creates the product, sets the price, and updates the description.
      WordPress: Publishes the AI-written blog article reviewing the product.
  Optimize Images: The workflow loops through every product image, updating them in WooCommerce with the new SEO-friendly metadata.

  How to set up
  Configure Credentials: Connect your Telegram, WooCommerce, WordPress, BrowserAct, Google Gemini, and OpenRouter accounts in n8n.
  Prepare BrowserAct: Ensure the WordPress & WooCommerce Product Management template is saved in your BrowserAct account.
  Configure Telegram: Create a bot via BotFather and add the API token to your Telegram credentials.
  Activate: Turn on the workflow.
  Test: Send a product link (e.g., from AliExpress or Amazon) to your bot to see it magically appear in your store and blog.

  Requirements
  BrowserAct* account with the *WordPress & WooCommerce Product Management** template.
  WooCommerce** account (Consumer Key/Secret).
  WordPress** account (Application Password).
  Telegram** account (Bot Token).
  Google Gemini* & *OpenRouter** accounts.

  How to customize the workflow
  Change Blog Tone: Modify the system prompt in the Generate response agent to change the writing style (e.g., "Professional Reviewer" vs. "Hypebeast").
  Add Social Media: Add a Twitter or LinkedIn node at the end to automatically tweet the new blog post link.
  Price Markup: Add a Code node before the WooCommerce step to automatically increase the scraped price by a percentage (margin).

  Need Help?
  How to Find Your BrowserAct API Key & Workflow ID
  How to Connect n8n to BrowserAct
  How to Use & Customize BrowserAct Templates
  Workflow Guidance and Showcase Video

  Automate WooCommerce: Auto-Import Products & Write Blog Posts with n8n 🚀

nodes_used:
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metadata_json:
  {"categories":["E-commerce","Marketing","Communication"],"complexity":"medium","use_cases":["Create WooCommerce products","Publish WordPress posts","Extract product data from links","Generate sales copy with AI","Create SEO-friendly blog articles"],"estimated_setup_minutes":15,"required_services":["WooCommerce","WordPress","Telegram","BrowserAct","Google Gemini","OpenRouter"],"key_features":["Automated product listing creation","AI-generated sales copy","SEO image metadata generation","Multi-platform content publishing","Browser automation for data extraction"],"target_audience":["E-commerce store owners","Dropshippers","Affiliate marketers"]}


name: Translate and dub YouTube videos using BrowserAct, Telegram, Gemini & ElevenLabs
author_name: Madame AI Team | Kai
author_username: madame-ai
categories: []
created_at: 2026-01-01T07:00:39.535Z
updated_at: 2026-01-01T07:00:39.535Z
url: https://n8n.io/workflows/12361
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Translate and dub YouTube videos using BrowserAct, Telegrma & Gemini

  This workflow transforms any YouTube video into a localized audio experience. It scrapes the video content, translates the transcript into your target language using AI, generates high-quality dubbed audio using ElevenLabs, and delivers the audio files and a summary directly to your Telegram chat.

  Target Audience
  Content creators, language learners, and educators looking to make video content accessible in multiple languages.

  How it works
  Receive Link: You send a YouTube video link to your Telegram bot.
  Extract URL: An AI Agent extracts the clean YouTube URL from your message.
  Scrape Content: BrowserAct executes a background task to fetch the video's transcript, description, and metadata.
  Translate & Script: A specialized AI Agent (using Google Gemini) translates the transcript into your chosen target language (e.g., Spanish). It also segments the text into logical parts for dubbing.
  Generate Audio: ElevenLabs synthesizes the translated text segments into natural-sounding speech.
  Deliver: The workflow sends the dubbed audio files and a translated summary post to your Telegram chat.

  How to set up
  Configure Credentials: Connect your Telegram, BrowserAct, ElevenLabs, and Google Gemini accounts in n8n.
  Prepare BrowserAct: Ensure the YouTube Translator & Auto Dubber template is saved in your BrowserAct account.
  Configure Telegram: Ensure your bot is created via BotFather and the API token is added to the Telegram credentials.
  Set Language: Open the Define Language node to set your desired target language (default is "Spanish").
  Activate: Turn on the workflow.
  Test: Send a YouTube link to your bot to start the dubbing process.

  Requirements
  BrowserAct* account with the *YouTube Translator & Auto Dubber** template.
  ElevenLabs** account.
  Telegram** account (Bot Token).
  Google Gemini** account.

  How to customize the workflow
  Change Voice: Open the Convert text to speech node and select a different ElevenLabs voice model.
  Add More Languages: Add logic to the Define Language node to let the user select a language via a Telegram menu.
  Change Output: Replace the Telegram output with a Google Drive node to save the audio files for later use.

  Need Help?
  How to Find Your BrowserAct API Key & Workflow ID
  How to Connect n8n to BrowserAct
  How to Use & Customize BrowserAct Templates

  Workflow Guidance and Showcase Video

  One-Click YouTube Translator: Auto-Dub Your YouTube Videos with n8n & ElevenLabs 🌍

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metadata_json:
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name: Generate YouTube thumbnails via Telegram using BrowserAct and Gemini (Nano Banana Pro)
author_name: Madame AI Team | Kai
author_username: madame-ai
categories: []
created_at: 2026-01-01T07:04:48.923Z
updated_at: 2026-01-01T07:04:48.923Z
url: https://n8n.io/workflows/12363
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Generate YouTube thumbnails via Telegram using BrowserAct & Nano banana Pro

  This workflow acts as an AI-powered "Viral Architect" for YouTube creators. Simply send a video topic (e.g., "Kling 2.6") to your Telegram bot, and it will scrape top-performing competitor thumbnails, analyze their visual strategies using AI vision, and generate a new, scientifically optimized thumbnail concept and image for you.

  Target Audience
  YouTubers, content creators, and social media managers looking to increase their Click-Through Rate (CTR) with AI-designed thumbnails.

  How it works
  Analyze Intent: The workflow receives a message via Telegram. An AI Agent classifies the input: is it a casual chat or a request for a thumbnail?
  Research Competitors: If a topic is detected, BrowserAct scrapes YouTube for the top-ranking videos on that subject.
  Visual Forensics: An AI Vision Agent (using OpenRouter/GPT-4o) analyzes the scraped thumbnails to understand why they work (colors, composition, text).
  User Approval: The bot sends a confirmation button to Telegram to ensure you want to proceed with image generation (saving credits).
  Creative Synthesis: Upon approval, a specialized Gemini Agent aggregates the research and crafts a high-fidelity prompt using psychological hooks and pop-culture references.
  Generate & Deliver: Google Gemini renders the final 4K thumbnail image, which is sent back to your Telegram chat.

  How to set up
  Configure Credentials: Connect your Telegram, BrowserAct, Google Sheets, OpenRouter, and Google Gemini accounts in n8n.
  Prepare BrowserAct: Ensure the Thumbnail Maker Bot template (or a YouTube search scraper) is saved in your BrowserAct account.
  Setup Google Sheet: Create a Google Sheet to store analysis data. The workflow will dynamically create tabs, but you need a master sheet ID.
  Configure Telegram: Ensure your bot is created via BotFather and the API token is added to the Telegram credentials.
  Activate: Turn on the workflow.

  Requirements
  BrowserAct* account with the *Thumbnail Maker Bot** template.
  Telegram** account (Bot Token).
  Google Sheets** account.
  OpenRouter** account (for Vision capabilities).
  Google Gemini** account.

  Google Sheets Requirements
  Spreadsheet Name:** Thumbnail Data base
  Sheet Name:** Database
  Required Columns:**
  Keyword
  Current Workflow Sheet ID

  How to customize the workflow
  Change Art Style: Modify the system prompt in the Generate Image Prompt agent to enforce a specific aesthetic (e.g., "3D Render," "Anime," "Minimalist").
  Adjust Research Depth: Change the number of videos scraped by BrowserAct to analyze more or fewer competitors.
  Add Text Overlay: Add an image processing node (like Cloudinary or Bannerbear) to automatically overlay the generated text onto the image for a final polish.

  Need Help?
  How to Find Your BrowserAct API Key & Workflow ID
  How to Connect n8n to BrowserAct 
  How to Use & Customize BrowserAct Templates

  Workflow Guidance and Showcase Video

  Automate Viral Thumbnails with n8n and AI Agents (Step-by-Step)

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metadata_json:
  {"categories":["Communication","Content Creation","Social Media Management"],"complexity":"medium","use_cases":["analyze competitor thumbnails","generate optimized thumbnails for YouTube","create viral marketing concepts","visual strategy analysis for social media"],"estimated_setup_minutes":30,"required_services":["BrowserAct","Opera GX","Google Gemini","Telegram"],"key_features":["AI vision analysis of competitor thumbnails","automated thumbnail generation","integrated chat-based workflow","structured image output","competitor scraping capabilities"],"target_audience":["YouTubers","content creators","social media managers"]}


name: Handle customer support queries with cache-first RAG using Redis, LangCache and OpenAI
author_name: Mohamed Abdelwahab
author_username: mohelwah
categories: []
created_at: 2026-01-02T15:09:23.547Z
updated_at: 2026-01-02T15:09:23.547Z
url: https://n8n.io/workflows/12400
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  An end-to-end Retrieval-Augmented Generation (RAG) customer support workflow for n8n, using a cache-first strategy (LangCache) combined with a Redis vector store powered by OpenAI embeddings.  
  This template is designed for fast, accurate, and cost-efficient customer support chatbots, internal help desks, and knowledge-base assistants.

  Overview

  This workflow implements a production-ready RAG architecture optimized for customer support use cases. Incoming chat messages are processed through a structured pipeline that prioritizes cached answers, falls back to semantic vector search when needed, and validates response quality before returning a final answer.

  The workflow supports:
  Multi-question user inputs
  Intelligent query decomposition
  Cache reuse to reduce latency and cost
  High-precision retrieval from a Redis vector database
  Quality evaluation and controlled retries
  Final answer synthesis into a single, coherent response

  Key Features

  Chat-based RAG pipeline** using n8n’s Chat Trigger
  Query decomposition** for multi-topic questions
  LangCache integration** (search + save)
  Redis Vector Store** for semantic retrieval
  OpenAI embeddings and chat models**
  Quality scoring** with retry logic
  Session memory buffers** for contextual continuity
  Fallback-safe behavior** (no hallucinations)

  How the Workflow Works

  1. Chat Trigger
  The workflow starts when a new chat message is received.

  2. Configuration Setup
  A centralized configuration node defines:
  LangCache base URL
  Cache ID
  Similarity threshold (default: 0.75)
  Maximum retrieval iterations (default: 2)

  3. Query Decomposition
  The user message is analyzed and decomposed into:
  A single focused question, or
  Multiple independent sub-questions

  This improves retrieval accuracy and cache reuse.

  4. Cache-First Retrieval
  Each sub-question is processed independently:
  The workflow first searches LangCache
  If a high-similarity cached answer is found, it is reused immediately

  5. Vector Retrieval (Cache Miss)
  If no cache hit exists:
  The query is embedded using OpenAI embeddings
  A semantic search is executed against the Redis vector index
  Retrieved knowledge-base documents are passed to a research-only agent

  6. Knowledge-Only Answering
  The research agent:
  Answers strictly from the retrieved knowledge
  Returns "no info found" if no relevant data exists

  7. Quality Evaluation
  Each generated answer is evaluated by a dedicated quality-check node:
  Outputs a numerical SCORE (0.0 – 1.0)
  Provides textual feedback
  Low scores can trigger limited retries

  8. Cache Update
  High-quality answers are saved back to LangCache for future reuse.

  9. Aggregation & Synthesis
  All sub-answers are aggregated and synthesized into:
  One final, user-facing response, or
  A polite fallback message if information is insufficient

  Main Nodes & Responsibilities

  When Chat Message Received** — Entry point for user messages
  LangCache Config** — Centralized configuration values
  Decompose Query (LangChain Agent)** — Splits complex queries
  Structured Output Parser** — Ensures valid JSON output
  Search LangCache** — Cache lookup via HTTP
  Redis Vector Store** — Semantic retrieval from Redis
  Embeddings OpenAI** — Vector generation
  Research Agent** — KB-only answering (no hallucinations)
  Quality Evaluator** — Scores answer relevance
  Save to LangCache** — Stores validated answers
  Memory Buffers** — Session context handling
  Response Synthesizer** — Final message generation

  Setup Instructions

  1. Configure Credentials
  Create the following credentials in n8n:
  OpenAI API**
  Redis**
  HTTP Bearer Auth** (for LangCache)

  2. Prepare the Knowledge Base
  Embed your documents using OpenAI embeddings
  Insert them into the configured Redis vector index
  Ensure documents are concise and well-structured

  3. Configure LangCache
  Update the configuration node with:
  langcacheBaseUrl
  langcacheCacheId
  Optional tuning for similarity threshold and iterations

  4. Test the Workflow
  Use the example data loader or schedule trigger
  Send test chat messages
  Validate cache hits, vector retrieval, and final responses

  Recommended Tuning

  Similarity Threshold:** 0.7 – 0.85
  Max Iterations:** 1 – 3
  Quality Score Cutoff:** 0.7
  Model Choice:** Use faster models for low latency, stronger models for accuracy
  Cache Policy:** Cache only high-confidence answers

  Security & Compliance Notes

  Store API keys securely using n8n credentials
  Avoid caching sensitive or personally identifiable information
  Apply least-privilege access to Redis and LangCache
  Consider logging cache writes for audit purposes

  Common Use Cases

  Customer support chatbots
  Internal help desks
  Knowledge-base assistants
  Self-service support portals
  AI-powered FAQ systems

  Template Metadata (Recommended)

  Template Name:** AI Customer Support — Redis RAG (LangCache + OpenAI)
  Category:** Customer Support / AI / RAG
  Tags:**  
    customer-support, RAG, knowledge-base, redis, openai, langcache, chatbot, n8n-template
  Difficulty Level:** Intermediate
  Required Integrations:** OpenAI, Redis, LangCache

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metadata_json:
  {"categories":["AI/ML"],"complexity":"medium","use_cases":["fast customer support","cost-efficient chatbots","knowledge-base assistants","internal help desks"],"estimated_setup_minutes":30,"required_services":["OpenAI","Redis"],"key_features":["cache-first architecture","vector store integration","structured output parsing","end-to-end RAG pipeline"],"target_audience":["customer support teams","AI engineers","developers"]}


name: Generate and publish Instagram carousels with Gemini and Google Slides
author_name: Bakdaulet Abdikhan
author_username: bakdaulet-abdikhan
categories: []
created_at: 2026-01-03T11:07:03.295Z
updated_at: 2026-01-03T11:07:03.295Z
url: https://n8n.io/workflows/12413
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Generate and publish Instagram carousels automatically
  Turn a single topic into a published Instagram Carousel in minutes.

  Creating educational carousel posts usually takes hours: writing the script, designing the slides in Figma/Canva, exporting images, and scheduling. This workflow automates the entire pipeline using Gemini AI, Google Slides, and the Meta Graph API.

  It generates the content, designs the visuals by manipulating a template, and publishes the carousel directly to your Instagram Business account.

  🚀 What this workflow does
  Script Generation: Runs daily (or on demand) to prompt Google Gemini to write a 6-slide educational script (Hook, Mistake, Why It Matters, Value, Tip, CTA).
  Design Automation:
     Copies a master Google Slides template.
     Uses a "Find & Replace" operation to insert the AI-generated text into the correct placeholders.
     Generates thumbnail images for each slide.
  Image Hosting: Uploads the slide images to ImgBB to get public URLs (required by Meta's API).
  Publishing:
     Creates a carousel container on Instagram using the Meta Graph API.
     Checks the container status until it is "FINISHED".
     Publishes the media to your feed.
  Logging: Records the post details, captions, and status in Google Sheets.

  💡 Key Features
  True Design Automation:** Doesn't just overlay text on images; it uses real Google Slides templates, allowing for complex layouts and branding.
  Smart Polling:** Includes a "Wait & Check" loop to ensure the media container is fully processed by Facebook before attempting to publish (prevents API errors).
  Structured Content:** The AI is prompted to follow a proven "Viral Educational" framework (Hook -&gt; Value -&gt; Action).
  Asset Management:** Automatically organizes generated slide images and links in Google Sheets for your archives.

  🛠️ Prerequisites
  Google Cloud:** Enabled APIs for Drive, Slides, Sheets, and Gemini.
  Meta Developer App:** An Instagram Business account connected to a Facebook Page, with a System User token (instagram_basic, instagram_content_publish, pages_read_engagement).
  ImgBB Account:** A free API key for temporary image hosting.
  Templates:** A Google Sheet and Google Slide template (links provided in the workflow sticky notes).

  📝 Setup Instructions
  Resources: Copy the provided Google Sheet and Slide templates to your Drive.
  Credentials: Authenticate Google, Meta, and ImgBB in n8n.
  Configuration:
     Update the Google Drive node with your Slide Template ID.
     Update the Google Sheets nodes with your Sheet ID.
     Update the HTTP Request nodes with your ImgBB API Key and Instagram Account ID.
  Run: Activate the schedule or click "Execute" to generate your first post!

  Need help setting this up or want a custom automation for your agency?
  I specialize in building agentic workflows for consultants and agencies.

  📧 Contact me: bakdaulet.mph@gmail.com

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name: Schedule appointments with manual approval using Google Calendar and Gmail
author_name: Shubham Mathur
author_username: smathur
categories: []
created_at: 2026-01-03T11:56:31.270Z
updated_at: 2026-01-03T11:56:31.270Z
url: https://n8n.io/workflows/12419
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Tired of automated booking tools cluttering your calendar with spam or overlapping meetings? SyncPoint is a “Smart Gatekeeper” that checks your availability and asks for your manual approval via email before a single event is booked. Once approved, it schedules the meeting automatically and notifies all stakeholders.

  Why use this?
  While most schedulers are fully automatic, they lack human intuition. SyncPoint bridges the gap. It automates the tedious parts (checking availability, generating meeting links, sending confirmations) but keeps you in control. If you're not feeling a specific meeting request, you can reject it with one click from your inbox.

  How it works?
  ++Webhook Trigger:++ Receives the appointment request (Name, Email, Organization, and Requested Time).

  ++Instant Response:++ Immediately responds to the requester via webhook (without waiting for approval), confirming the request is under review.

  ++Availability Check:++ The workflow automatically queries your Google Calendar for a 1-hour window starting at the requested time.

  ++Smart Branching:++

  If Busy: It immediately ends the process (or can be configured to send a "Slot Taken" email).

  If Free: It sends an Approval Email to your inbox using the Gmail sendAndWait node.

  Human-in-the-Loop: You receive an email with "Approve" and "Reject" buttons. The workflow pauses safely (up to 1 hour) using an async wait mechanism and resumes automatically once a decision is made.

  ++Final Execution:++

  Approved: It creates the Google Calendar event, generates a Google Meet link, and sends a confirmation email to the client.

  Rejected: It sends a polite "Not available" email to the client and clears the workflow.

  Requirements
  To get this workflow running, you will need:

  Google Calendar OAuth2 API: To verify availability and create the final event.

  Gmail OAuth2 API: To send the approval request to yourself and the final status to the client.

  Publicly accessible n8n instance: Since this uses a Webhook and the Wait for Link functionality, your n8n instance must be reachable from the internet. It could be self hosted or n8n cloud itself.

  Setup Instructions

  Credentials: Connect your Google Calendar and Gmail accounts in the n8n credentials manager.
  Configure the Admin Email:
     Open the "Get Approval (HR)" node.
     Change the To Email field to your own email address where you want to receive the approval requests.

  Webhook Body:
  [
    {
      "params": {
        
      },
      "query": {
        
      },
      "body": {
        "name": "Jon Doe",
        "organization": "Test Org",
        "email": "test@test.com",
        "phone": "9999999999",
        "appointmentDateTime": "2026-01-20T20:00:00+05:30",
        "optionalMessage": "I'm interested in the AI-Powered Systems plan."
      },
      "webhookUrl": "https://america-gavialoid-claudio.ngrok-free.dev/webhook-test/appointment-request",
      "executionMode": "test"
    }
  ]
  Timezone Configuration: The workflow is currently set to Asia/Kolkata (+05:30).
       To change this, open the "Mapping" and "Check Availability" nodes and update the timezone string to your local timezone (e.g., America/New_York).
    
  Calendar Selection: In the "Check Availability" and "Book Appointment" nodes, ensure the Calendar field is pointed to your primary email calendar.

  Customization Ideas
  Dynamic Duration:** Add a field to the Webhook for "Meeting Length" and use it to calculate the end time dynamically.
  Slack/Discord Notifications:** Instead of Gmail, use a Slack "Wait for Interaction" node to approve or reject meetings directly from a chat channel.
  Buffer Times:** Adjust the availability check to look for a 1.5-hour window instead of 1 hour to ensure you have a "breathing room" between meetings.

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name: Find cheap flight deals using Google Gemini, GPT-4, Telegram and BrowserAct
author_name: Madame AI Team | Kai
author_username: madame-ai
categories: []
created_at: 2026-01-03T20:17:44.753Z
updated_at: 2026-01-03T20:17:44.753Z
url: https://n8n.io/workflows/12435
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Find cheap flight deals using AI, Telegram and BrowserAct

  This workflow transforms your Telegram bot into an intelligent travel agent. Ask for deals (e.g., "Flights from Berlin"), and it will scrape real-time prices from a flight aggregator, curate the best offers using AI, and deliver a formatted list directly to your chat.

  Target Audience
  Travel enthusiasts, digital nomads, and budget-conscious flyers looking for automated deal alerts.

  How it works
  Receive Request: You send a message to your Telegram bot (e.g., "Cheap flights from London").
  Extract Location: An AI Agent parses your message to identify the departure city. If you don't specify one, it asks for clarification.
  Scrape Deals: BrowserAct executes a background task to search a flight aggregator (like Momondo or Skyscanner) for the best deals from your chosen city.
  Curate & Format: A second AI Agent processes the raw flight data. It sorts deals by price, groups them for readability, adds country flags, and formats the list into Telegram-friendly HTML.
  Deliver: The workflow splits the curated list into multiple messages (if necessary) and sends them to your Telegram chat.

  How to set up
  Configure Credentials: Connect your Telegram, BrowserAct, Google Gemini, and OpenRouter accounts in n8n.
  Prepare BrowserAct: Ensure the Low-Cost Travel Finder template is saved in your BrowserAct account.
  Configure Telegram: Ensure your bot is created via BotFather and the API token is added to the Telegram credentials.
  Activate: Turn on the workflow.
  Test: Send a message like "Flights from NYC" to your bot.

  Requirements
  BrowserAct* account with the *Low-Cost Travel Finder** template.
  Telegram** account (Bot Token).
  Google Gemini* & *OpenRouter** accounts.

  How to customize the workflow
  Filter by Destination: Add logic to the Generate response agent to only show flights to specific regions (e.g., "Only show Asia destinations").
  Change Aggregator: Update the BrowserAct template to scrape Google Flights or Kayak instead of Momondo.
  Set Alerts: Add a Schedule Trigger to run this workflow automatically every morning for your home airport.

  Need Help?
  How to Find Your BrowserAct API Key & Workflow ID
  How to Connect n8n to BrowserAct
  How to Use & Customize BrowserAct Templates

  Workflow Guidance and Showcase Video

  Build a Low-Cost Flight Finder with n8n & AI (Telegram Bot Tutorial)

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name: Auto-post curated remote jobs to Telegram with BrowserAct and Gemini
author_name: Madame AI Team | Kai
author_username: madame-ai
categories: []
created_at: 2026-01-03T20:21:31.879Z
updated_at: 2026-01-03T20:21:31.879Z
url: https://n8n.io/workflows/12436
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Auto-post curated remote jobs to Telegram with BrowserAct & Gemini

  This workflow acts as an intelligent job board curator for your Telegram community. It scrapes multiple sources (Remotive, SimplyHired), uses AI to filter out spam and low-quality listings, formats the best jobs into professional posts, and publishes them automatically on a schedule.

  Target Audience
  Community managers running job boards, recruiters, and developers building niche job aggregators.

  How it works
  Scheduled Fetch: Every 12 hours, the workflow triggers BrowserAct to scrape the latest job listings from Remotive and SimplyHired in parallel.
  Merge & Aggregate: The raw job data from both sources is combined into a single list.
  AI Curation: An AI Agent (using Google Gemini) reviews each job. It removes duplicates, filters out gigs paying less than $20/hr, and discards low-quality descriptions.
  Format Content: The AI rewrites the remaining jobs into clean, engaging HTML summaries suitable for Telegram.
  Publish: The workflow loops through the curated list and sends each job to your Telegram channel, pausing between messages to avoid rate limits.

  How to set up
  Configure Credentials: Connect your Telegram, BrowserAct, and Google Gemini accounts in n8n.
  Prepare BrowserAct: Ensure you have the Automated Remote Job Fetching & Filtering for Telegram Feed templates (for Remotive and SimplyHired) saved in your BrowserAct account.
  Configure Telegram: Ensure your bot is an admin in the target channel and add the Chat ID to the Send a text message node.
  Activate: Turn on the workflow.

  Requirements
  BrowserAct* account with the *Automated Remote Job Fetching & Filtering for Telegram Feed** templates.
  Telegram** account (Bot Token).
  Google Gemini** account.

  How to customize the workflow
  Add More Sources: Duplicate the BrowserAct nodes to scrape additional sites like We Work Remotely or LinkedIn.
  Refine Filters: Update the system prompt in the AI Agent node to filter by specific keywords (e.g., "Python", "Senior") or locations.
  Change Frequency: Adjust the Schedule Trigger to run more or less frequently depending on your needs.

  Need Help?
  How to Find Your BrowserAct API Key & Workflow ID
  How to Connect n8n to BrowserAct
  How to Use & Customize BrowserAct Templates

  Workflow Guidance and Showcase Video

  Build an AI-Powered Remote Job Aggregator (Remotive & SimplyHired)

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name: Automated PDF & Image Text Extractor & Instant Social Media Posting
author_name: SpaGreen Creative
author_username: spagreen
categories: []
created_at: 2026-01-04T09:39:16.673Z
updated_at: 2026-01-04T09:39:16.673Z
url: https://n8n.io/workflows/12447
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Who is this for?
  This workflow is designed for content creators, social media managers, digital marketers, and business owners who want to automate their content creation and distribution process across multiple platforms. It's perfect for those who regularly create content from PDFs or images and want to streamline their social media posting workflow.

  Key Features
  Monitors a specific Google Drive folder for new PDFs or images
  Extracts text from PDFs or images using AI
  Optionally generates new images from text using OpenAI's DALL-E
  Automatically posts content with images to multiple platforms
  Sends notifications about successful posts
  Handles different file types with specialized extraction methods

  Workflow Does
  This workflow automates monitoring a Google Drive folder for new PDFs and images, extracting content using AI, and distributing it across social media platforms like WordPress, Facebook, Telegram, LinkedIn, and Discord. It can also generate new images from text and sends notifications about successful posts. The process ensures efficient handling of different file types and streamlines content sharing across multiple channels.

  Requirements
  Google Drive account with a dedicated folder for content
  OpenAI API credentials for image generation
  WordPress API credentials for website posting
  Social media API credentials:
    Facebook Graph API
    Telegram Bot API
    LinkedIn OAuth2 API
    Discord Bot API
    X/Twitter OAuth2 API
  Gmail credentials for email notifications
  Rapiwa account for WhatsApp notifications

  Important Notes
  Make sure all API credentials are properly configured before running the workflow
  The workflow handles both PDF and image files differently based on their MIME type
  Image generation is optional and can be disabled if not needed
  All social media posting nodes can be individually enabled or disabled based on your needs
  The workflow includes rate limiting to avoid API restrictions

  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: Create AI product images and marketing videos with NanoBanana Pro, Veo 3.1 and Blotato
author_name: Dr. Firas
author_username: drfiras
categories: []
created_at: 2026-01-04T22:28:11.506Z
updated_at: 2026-01-04T22:28:11.506Z
url: https://n8n.io/workflows/12462
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:21
description:
  💥 Generate product images with NanoBanana Pro to Veo videos and Blotato

  Who is this for?

  This workflow is designed for:
  Content creators and marketers
  E-commerce and product-based businesses
  Agencies producing social media visuals and videos
  Automation builders looking for AI-powered creative pipelines

  It is ideal for anyone who wants to automate product image and video creation using AI and publish content without manual work.

  What problem is this workflow solving? / Use case

  Creating product visuals and marketing videos usually requires multiple tools, manual prompt writing, and repetitive steps.

  This workflow solves:
  Manual image and video creation
  Inconsistent visual quality across assets
  Time-consuming prompt iteration
  Manual video publishing to social platforms

  The workflow automates the entire process from image generation to video publishing using AI.

  What this workflow does

  This workflow provides an end-to-end automation pipeline:

  Generates high-quality product images using NanoBanana Pro
  Applies Contact Sheet Prompting to explore multiple visual variations
  Converts selected images into short marketing videos using Veo 3.1
  Automatically publishes the final videos via BLOTATO

  The result is a fully automated creative workflow that turns AI prompts into ready-to-publish video content.

  Setup

  To use this workflow, you need the following services and credentials:

  OpenAI API**
    Used for image analysis and prompt generation
  NanoBanana Pro (fal.ai)**
    Product image generation  
    API: https://fal.ai/models/fal-ai/nano-banana-pro/edit/api
  Veo 3.1 (fal.ai)**
    Video generation  
    API: https://fal.ai/models/fal-ai/veo3.1/first-last-frame-to-video
  Blotato**
    Video publishing to social platforms  
    Sign up at BLOTATO

  All credentials must be added in n8n before running the workflow.

  How to customize this workflow to your needs

  You can easily adapt this workflow by:
  Modifying AI prompts to match your brand style
  Adjusting image composition and realism parameters in NanoBanana Pro
  Changing video motion, pacing, and aspect ratio in Veo 3.1
  Selecting different social platforms or publishing rules in Blotato
  Replacing or extending individual steps while keeping the same architecture

  The workflow is modular and can be reused for multiple products or campaigns.

  🎥 Watch This Tutorial

  👋 Need help or want to customize this?
  📩 Contact: LinkedIn  
  📺 YouTube: @DRFIRASS  
  🚀 Workshops: Mes Ateliers n8n

  📄 Documentation: Notion Guide
  Need help customizing?
  Contact me for consulting and support : Linkedin / Youtube / 🚀 Mes Ateliers n8n  

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metadata_json:
  {"categories":["Marketing","Content Creation"],"complexity":"medium","use_cases":["Generate AI product images","Create marketing videos","Automate social media visuals","Orchestrate creative AI pipelines"],"estimated_setup_minutes":15,"required_services":["NanoBanana Pro","Veo 3.1","Blotato","Google Drive","Spreadsheets"],"key_features":["Multi-modal AI generation","Automated content pipelines","Integrated video and image creation","Cloud storage integration"],"target_audience":["Content creators","Marketers","Agencies"]}


