Workflow Templates

📊 Description Ensure your GitHub repositories stay configuration-accurate and documentation-compliant with this intelligent AI-powered validation workflow. 🤖 This automation monitors repository updates, compares configuration files against documentation references, detects inconsistencies, and alerts your team instantly—streamlining DevOps and compliance reviews. ⚡ What This Template Does Step 1: Triggers automatically on GitHub push or pull_request events. 🔄 Step 2: Fetches both configuration files (config/app-config.json and faq-config.json) from the repository. 📂 Step 3: Uses GPT-4o-mini to compare configurations and detect mismatches, missing keys, or deprecated fields. 🧠 Step 4: Categorizes issues by severity—critical, high, medium, or low—and generates actionable recommendations. 🚨 Step 5: Logs all discrepancies to Google Sheets for tracking and audit purposes. 📑 Step 6: Sends Slack alerts summarizing key issues and linking to the full report. 💬 Key Benefits ✅ Prevents production incidents due to config drift ✅ Ensures documentation stays in sync with code changes ✅ Reduces manual review effort with AI-driven validation ✅ Improves team response with Slack-based alerts ✅ Maintains audit logs for compliance and traceability Features Real-time GitHub webhook integration AI-powered config comparison using GPT-4o-mini Severity-based issue classification Automated Google Sheets logging Slack alerts with detailed issue context Error handling for malformed JSON or parsing issues Requirements GitHub OAuth2 credentials with repo and webhook permissions OpenAI API key (GPT-4o-mini or compatible model) Google Sheets OAuth2 credentials Slack API token with chat:write permissions Target Audience DevOps teams ensuring consistent configuration across environments Engineering leads maintaining documentation accuracy QA and Compliance teams tracking configuration changes and risks Setup Instructions Create GitHub OAuth2 credentials and enable webhook access. Connect your OpenAI API key under credentials. Add your Google Sheets and Slack integrations. Update file paths (config/app-config.json and faq-config.json) if your repo uses different names. Activate the workflow — it will start validating on every push or PR. 🚀

📘 Code of Conduct Q&A Slack Chatbot with RAG Powered > Empower employees to instantly access and understand the company’s Code of Conduct via a Slack chatbot, powered by Retrieval-Augmented Generation (RAG) and LLMs. 🧑‍💼 Who’s it for This workflow is designed for: HR and compliance teams** to automate policy-related inquiries Employees** who want quick answers to Code of Conduct questions directly inside Slack Startups or enterprises** that need internal compliance self-service tools powered by AI ⚙️ How it works / What it does This RAG-powered Slack chatbot answers user questions based on your uploaded Code of Conduct PDF using GPT-4 and embedded document chunks. Here's the flow: Receive Message from Slack: A webhook triggers when a message is posted in Slack. Check if it’s a valid query: Filters out non-user messages (e.g., bot mentions). Run Agent with RAG: Uses GPT-4 with Query Data Tool to retrieve relevant document chunks. Returns a well-formatted, context-aware answer. Send Response to Slack: Fetches user info and posts the answer back in the same channel. Document Upload Flow: HR can upload the PDF Code of Conduct file. It’s parsed, chunked, embedded using OpenAI, and stored for future query retrieval. A backup copy is saved to Google Drive. 🛠️ How to set up Prepare your environment: Slack Bot token & webhook configured (Sample slack app manifest: https://wisestackai.s3.ap-southeast-1.amazonaws.com/slack_bot_manifest.json) OpenAI API key (for GPT-4 & embedding) Google Drive credentials (optional for backup) Upload the Code of Conduct PDF: Use the designated node to upload your document (Sample file: https://wisestackai.s3.ap-southeast-1.amazonaws.com/20220419-ingrs-code-of-conduct-policy-en.pdf) This triggers chunking → embedding → data store. Deploy the chatbot: Host the webhook and connect it to your Slack app. Share the command format with employees (e.g., @CodeBot Can I accept gifts from partners?) Monitor and iterate: Improve chunk size or embed model if queries aren’t accurate. Review unanswered queries to enhance coverage. 📋 Requirements n8n (Self-hosted or Cloud) Slack App (with chat:write, users:read, commands) OpenAI account (embedding + GPT-4 access) Google Drive integration (for backups) Uploaded Code of Conduct in PDF format 🧩 How to customize the workflow | What to Customize | How to Do It | |-----------------------------|------------------------------------------------------------------------------| | 🔤 Prompt style | Edit the System & User prompts inside the Code Of Conduct Agent node | | 📄 Document types | Upload additional policy PDFs and tag them differently in metadata | | 🤖 Agent behavior | Tune GPT temperature or replace with different LLM | | 💬 Slack interaction | Customize message formats or trigger phrases | | 📁 Data Store engine | Swap to Pinecone, Weaviate, Supabase, etc. depending on use case | | 🌐 Multilingual support | Preprocess text and support locale detection via Slack metadata |

Decodo Amazon Product Recommender delivers instant, AI-powered shopping recommendations directly through Telegram. Send any product name and receive Amazon product analysis featuring price comparisons, ratings, sales data, and categorized recommendations (budget, premium, best value) in under 40 seconds—eliminating hours of manual research. Why Use This Workflow? Time Savings: Reduce product research from 45+ minutes to under 30 seconds Decision Quality: Compare 20+ products automatically with AI-curated recommendations Zero Manual Work: Complete automation from message input to formatted recommendations Ideal For E-commerce Entrepreneurs:** Quickly research competitor products, pricing strategies, and market trends for inventory decisions Smart Shoppers & Deal Hunters:** Get instant product comparisons with sales volume data and discount tracking before purchasing Product Managers & Researchers:** Analyze Amazon marketplace positioning, customer sentiment, and pricing ranges for competitive intelligence How It Works Trigger: User sends product name via Telegram (e.g., "iPhone 15 Pro Max case") AI Validation: Gemini 2.5 Flash extracts core product keywords and validates input authenticity Data Collection: Decodo API scrapes Amazon search results, extracting prices, ratings, reviews, sales volume, and product URLs Processing: JavaScript node cleans data, removes duplicates, calculates value scores, and categorizes products (top picks, budget, premium, best value, most popular) Intelligence Layer: AI generates personalized recommendations with Telegram-optimized markdown formatting, shortened product names, and clean Amazon URLs Output & Delivery: Formatted recommendations sent to user with categorized options and direct purchase links Error Handling: Admin notifications via separate Telegram channel for workflow monitoring Setup Guide Prerequisites | Requirement | Type | Purpose | |-------------|------|---------| | n8n instance | Essential | Workflow execution platform | | Decodo Account | Essential | Amazon product data scraping | | Telegram Bot Token | Essential | Chat interface for user interactions | | Google Gemini API | Essential | AI-powered product validation and recommendations | | Telegram Account | Optional | Admin error notifications | Installation Steps Import the JSON file to your n8n instance Configure credentials: Decodo API: Sign up at decodo.com → Dashboard → Scraping APIs → Web Advanced → Copy BASIC AUTH TOKEN Telegram Bot: Message @BotFather on Telegram → /newbot → Copy HTTP API token (format: 123456789:ABCdefGHI...) Google Gemini: Obtain API key from Google AI Studio for Gemini 2.5 Flash model Update environment-specific values: Replace YOUR-CHAT-ID in "Notify Admin" node with your Telegram chat ID for error notifications Verify Telegram webhook IDs are properly configured Customize settings: Adjust AI prompt in "Generate Recommendations" node for different output formats Set character limits (default: 2500) for Telegram message length Test execution: Send test message to your Telegram bot: "iPhone 15 Pro" Verify processing status messages appear Confirm recommendations arrive with properly formatted links Customization Options Basic Adjustments: Character Limit**: Modify 2500 in AI prompt to adjust response length (Telegram max: 4096) Advanced Enhancements: Multi-language Support**: Add language detection and translation nodes for international users Price Tracking**: Integrate Google Sheets to log historical prices and trigger alerts on drops Image Support**: Enable Telegram photo messages with product images from scraping results Troubleshooting Common Issues: | Problem | Cause | Solution | |---------|-------|----------| | "No product detected" for valid inputs | AI validation too strict or ambiguous query | Add specific product details (model number, brand) in user input | | Empty recommendations returned | Decodo API rate limit or Amazon blocking | Wait 60 seconds between requests; verify Decodo account status | | Telegram message formatting broken | Special characters in product names | Ensure Telegram markdown mode is set to "Markdown" (legacy) not "MarkdownV2" | Use Case Examples Scenario 1: E-commerce Store Owner Challenge: Needs to quickly assess competitor pricing and product positioning for new inventory decisions without spending hours browsing Amazon Solution: Sends "wireless earbuds" to bot, receives categorized analysis of 20+ products with price ranges ($15-$250), top sellers, and discount opportunities Result: Identifies $35-$50 price gap in market, sources comparable product, achieves 40% profit margin Scenario 2: Smart Shopping Enthusiast Challenge: Wants to buy a laptop backpack but overwhelmed by 200+ Amazon options with varying prices and unclear value propositions Solution: Messages "laptop backpack" to bot, gets AI recommendations sorted by budget ($30), premium ($50+), best value (highest discount + good ratings), and most popular (by sales volume) Result: Purchases "Best Value" recommendation with 35% discount, saves $18 and 45 minutes of research time Created by: Khaisa Studio Category: AI | Productivity | E-commerce | Tags: amazon, telegram, ai, product-research, shopping, automation, gemini Need custom workflows? Contact us Connect with the creator: Portfolio • Workflows • LinkedIn • Medium • Threads

Product Price Monitor with Mailgun and MongoDB ⚠️ COMMUNITY TEMPLATE DISCLAIMER: This is a community-contributed template that uses ScrapeGraphAI (a community node). Please ensure you have the ScrapeGraphAI community node installed in your n8n instance before using this template. This workflow automatically scrapes multiple e-commerce sites, records weekly product prices in MongoDB, analyzes seasonal trends, and emails a concise report to retail stakeholders via Mailgun. It helps retailers make informed inventory and pricing decisions by providing up-to-date pricing intelligence. Pre-conditions/Requirements Prerequisites n8n instance (self-hosted, desktop, or n8n.cloud) ScrapeGraphAI community node installed and activated MongoDB database (Atlas or self-hosted) Mailgun account with a verified domain Publicly reachable n8n Webhook URL (if self-hosted) Required Credentials ScrapeGraphAI API Key** – Enables web scraping across target sites MongoDB Credentials** – Connection string (MongoDB URI) with read/write access Mailgun API Key & Domain** – To send summary emails MongoDB Collection Schema | Field | Type | Example Value | Notes | |-----------------|----------|---------------------------|---------------------------------------------| | productId | String | SKU-12345 | Unique identifier you define | | productName | String | Women's Winter Jacket | Human-readable name | | timestamp | Date | 2024-09-15T00:00:00Z | Ingest date (automatically added) | | price | Number | 79.99 | Scraped price | | source | String | example-shop.com | Domain where price was scraped | How it works This workflow automatically scrapes multiple e-commerce sites, records weekly product prices in MongoDB, analyzes seasonal trends, and emails a concise report to retail stakeholders via Mailgun. It helps retailers make informed inventory and pricing decisions by providing up-to-date pricing intelligence. Key Steps: Webhook Trigger**: Starts the workflow on a scheduled HTTP call or manual trigger. Code (Prepare Products)**: Defines the list of SKUs/URLs to monitor. Split In Batches**: Processes products in manageable chunks to respect rate limits. ScrapeGraphAI (Scrape Price)**: Extracts price, availability, and currency from each product URL. Merge (Combine Results)**: Re-assembles all batch outputs into one dataset. MongoDB (Upsert Price History)**: Stores each price point for historical analysis. If (Seasonal Trend Check)**: Compares current price against historical average to detect anomalies. Set (Email Payload)**: Formats the trend report for email. Mailgun (Send Email)**: Emails weekly summary to specified recipients. Respond to Webhook**: Returns “200 OK – Report Sent” response for logging. Set up steps Setup Time: 15-20 minutes Install Community Node In n8n, go to “Settings → Community Nodes” and install @n8n-community/nodes-scrapegraphai. Create Credentials Add ScrapeGraphAI API key under Credentials. Add MongoDB credentials (type: MongoDB). Add Mailgun credentials (type: Mailgun). Import Workflow Download the JSON template, then in n8n click “Import” and select the file. Configure Product List Open the Code (Prepare Products) node and replace the example array with your product objects { id, name, url }. Adjust Cron/Schedule If you prefer a fully automated schedule, replace the Webhook with a Cron node (e.g., every Monday at 09:00). Verify MongoDB Collection Ensure the collection (default: productPrices) exists or let n8n create it on first run. Set Recipients In the Mailgun node, update the to, from, and subject fields. Execute Test Run Manually trigger the Webhook URL or run the workflow once to verify data flow and email delivery. Activate Toggle the workflow to “Active” so it runs automatically each week. Node Descriptions Core Workflow Nodes: Webhook** – Entry point that accepts a GET/POST call to start the job. Code (Prepare Products)** – Outputs an array of products to monitor. Split In Batches** – Limits scraping to N products per request to avoid banning. ScrapeGraphAI** – Scrapes the HTML of a product page and parses pricing data. Merge** – Re-combines batch results for streamlined processing. MongoDB** – Inserts or updates each product’s price history document. If** – Determines whether price deviates > X% from the season average. Set** – Builds an HTML/text email body containing the findings. Mailgun** – Sends the email via Mailgun REST API. Respond to Webhook** – Returns an HTTP response for logging/monitoring. Sticky Notes** – Provide in-workflow documentation (no execution). Data Flow: Webhook → Code → Split In Batches Split In Batches → ScrapeGraphAI → Merge Merge → MongoDB → If If (true) → Set → Mailgun → Respond to Webhook Customization Examples Change Scraping Frequency (Cron) // Cron node settings { "mode": "custom", "cronExpression": "0 6 * * 1,4" // Monday & Thursday 06:00 } Extend Data Points (Reviews Count, Stock) // In ScrapeGraphAI extraction config { "price": "css:span.price", "inStock": "css:div.availability", "reviewCount": "regex:\"(\\d+) reviews\"" } Data Output Format The workflow outputs structured JSON data: { "productId": "SKU-12345", "productName": "Women's Winter Jacket", "timestamp": "2024-09-15T00:00:00Z", "price": 79.99, "currency": "USD", "source": "example-shop.com", "trend": "5% below 3-month average" } Troubleshooting Common Issues ScrapeGraphAI returns empty data – Confirm selectors/XPath are correct; test with ScrapeGraphAI playground. MongoDB connection fails – Verify IP-whitelisting for Atlas or network connectivity for self-hosted instance. Mail not delivered – Check Mailgun logs for bounce or spam rejection, and ensure from domain is verified. Performance Tips Use smaller batch sizes (e.g., 5 URLs) to avoid target site rate-limit blocks. Cache static product info; scrape only fields that change (price, stock). Pro Tips: Integrate the IF node with n8n’s Slack node to push urgent price drops to a channel. Add a Function node to calculate moving averages for deeper analysis. Store raw HTML snapshots in S3/MinIO for auditability and debugging.

Decodo Amazon Product Recommender delivers instant, AI-powered shopping recommendations directly through Telegram. Send any product name and receive Amazon product analysis featuring price comparisons, ratings, sales data, and categorized recommendations (budget, premium, best value) in under 40 seconds—eliminating hours of manual research. Why Use This Workflow? Time Savings: Reduce product research from 45+ minutes to under 30 seconds Decision Quality: Compare 20+ products automatically with AI-curated recommendations Zero Manual Work: Complete automation from message input to formatted recommendations Ideal For E-commerce Entrepreneurs:** Quickly research competitor products, pricing strategies, and market trends for inventory decisions Smart Shoppers & Deal Hunters:** Get instant product comparisons with sales volume data and discount tracking before purchasing Product Managers & Researchers:** Analyze Amazon marketplace positioning, customer sentiment, and pricing ranges for competitive intelligence How It Works Trigger: User sends product name via Telegram (e.g., "iPhone 15 Pro Max case") AI Validation: Gemini 2.5 Flash extracts core product keywords and validates input authenticity Data Collection: Decodo API scrapes Amazon search results, extracting prices, ratings, reviews, sales volume, and product URLs Processing: JavaScript node cleans data, removes duplicates, calculates value scores, and categorizes products (top picks, budget, premium, best value, most popular) Intelligence Layer: AI generates personalized recommendations with Telegram-optimized markdown formatting, shortened product names, and clean Amazon URLs Output & Delivery: Formatted recommendations sent to user with categorized options and direct purchase links Error Handling: Admin notifications via separate Telegram channel for workflow monitoring Setup Guide Prerequisites | Requirement | Type | Purpose | |-------------|------|---------| | n8n instance | Essential | Workflow execution platform | | Decodo Account | Essential | Amazon product data scraping | | Telegram Bot Token | Essential | Chat interface for user interactions | | Google Gemini API | Essential | AI-powered product validation and recommendations | | Telegram Account | Optional | Admin error notifications | Installation Steps Import the JSON file to your n8n instance Configure credentials: Decodo API: Sign up at decodo.com → Dashboard → Scraping APIs → Web Advanced → Copy BASIC AUTH TOKEN Telegram Bot: Message @BotFather on Telegram → /newbot → Copy HTTP API token (format: 123456789:ABCdefGHI...) Google Gemini: Obtain API key from Google AI Studio for Gemini 2.5 Flash model Update environment-specific values: Replace YOUR-CHAT-ID in "Notify Admin" node with your Telegram chat ID for error notifications Verify Telegram webhook IDs are properly configured Customize settings: Adjust AI prompt in "Generate Recommendations" node for different output formats Set character limits (default: 2500) for Telegram message length Test execution: Send test message to your Telegram bot: "iPhone 15 Pro" Verify processing status messages appear Confirm recommendations arrive with properly formatted links Customization Options Basic Adjustments: Character Limit**: Modify 2500 in AI prompt to adjust response length (Telegram max: 4096) Advanced Enhancements: Multi-language Support**: Add language detection and translation nodes for international users Price Tracking**: Integrate Google Sheets to log historical prices and trigger alerts on drops Image Support**: Enable Telegram photo messages with product images from scraping results Troubleshooting Common Issues: | Problem | Cause | Solution | |---------|-------|----------| | "No product detected" for valid inputs | AI validation too strict or ambiguous query | Add specific product details (model number, brand) in user input | | Empty recommendations returned | Decodo API rate limit or Amazon blocking | Wait 60 seconds between requests; verify Decodo account status | | Telegram message formatting broken | Special characters in product names | Ensure Telegram markdown mode is set to "Markdown" (legacy) not "MarkdownV2" | Use Case Examples Scenario 1: E-commerce Store Owner Challenge: Needs to quickly assess competitor pricing and product positioning for new inventory decisions without spending hours browsing Amazon Solution: Sends "wireless earbuds" to bot, receives categorized analysis of 20+ products with price ranges ($15-$250), top sellers, and discount opportunities Result: Identifies $35-$50 price gap in market, sources comparable product, achieves 40% profit margin Scenario 2: Smart Shopping Enthusiast Challenge: Wants to buy a laptop backpack but overwhelmed by 200+ Amazon options with varying prices and unclear value propositions Solution: Messages "laptop backpack" to bot, gets AI recommendations sorted by budget ($30), premium ($50+), best value (highest discount + good ratings), and most popular (by sales volume) Result: Purchases "Best Value" recommendation with 35% discount, saves $18 and 45 minutes of research time Created by: Khaisa Studio Category: AI | Productivity | E-commerce | Tags: amazon, telegram, ai, product-research, shopping, automation, gemini Need custom workflows? Contact us Connect with the creator: Portfolio • Workflows • LinkedIn • Medium • Threads

Icebreaker Generator powered with ChatGPT This n8n template crawls a company website, distills the content with AI, and produces a short, personalized icebreaker you can drop straight into your cold emails or CRM. Perfect for SDRs, founders, and agencies who want “real research” at scale. Good to know Works from a Google Sheet of leads (domain + LinkedIn, etc.). Handles common scrape failures gracefully and marks the lead’s Status as Error. Uses ChatGPT to summarize pages and craft one concise, non-generic opener. Output is written back to the same Google Sheet (IceBreaker, Status). You’ll need Google credentials (for Sheets) and OpenAI credentials (for GPT). How it works Step 1 — Discover internal pages Reads a lead’s website from Google Sheets. Scrapes the home page and extracts all links. A Code node cleans the list (removes emails/anchors/social/external domains, normalizes paths, de-duplicates) and returns unique internal URLs. If the home page is unreachable or no links are found, the lead is marked Error and the workflow moves on. Step 2 — Convert pages to text Visits each collected URL and converts the response into HTML/Markdown text for analysis. You can cap depth/amount with the Limit node. Step 3 — Summarize & generate the icebreaker A GPT node produces a two-paragraph abstract for each page (JSON output). An Aggregate node merges all abstracts for the company. Another GPT node turns the merged summary into a personalized, multi-line icebreaker (spartan tone, non-obvious details). The result is written back to Google Sheets (IceBreaker = ..., Status = Done). The workflow loops to the next lead. How to use Prepare your sheet Include at least: organization_website_url, linkedin_url, and any other lead fields you track. Keep an empty IceBreaker and Status column for the workflow to fill. Connect credentials Google Sheets: use the Google account that owns the sheet and link it in the nodes. OpenAI: add your API key to the GPT nodes (“Summarize Website Page”, “Generate Multiline Icebreaker”). Run the workflow Start with the Manual Trigger (or replace with a schedule/webhook). Adjust Limit if you want fewer/more pages per company. Watch Status (Done/Error) and IceBreaker populate in your sheet. Requirements n8n instance Google Sheets account & access to the leads sheet OpenAI API key (for summarization + icebreaker generation) Customizing this workflow Tone & format: tweak the prompts (both GPT nodes) to match your brand voice and structure. Depth: change the Limit node to scan more/less pages; add simple rules to prioritize certain paths (e.g., /about, /blog/*). Fields: write additional outputs (e.g., Company Summary, Key Products, Recent News) back to new sheet columns. Lead selection: filter rows by Status = "" (or custom flags) to only process untouched leads. Error handling: expand the Error branch to retry with www./HTTP→HTTPS or to log diagnostics in a separate tab. Tips Keep icebreakers short, specific, and free of clichés—small, non-obvious details from the site convert best. Start with a small batch to validate quality, then scale up. Consider adding a rate limit if target sites throttle requests. In short: Sheet → crawl internal pages → AI abstracts → single tailored icebreaker → write back to the sheet, then repeat for the next lead. This automation can work great with our automation for automated cold emailing.

🚀 Enrich CRM Leads with LinkedIn Company Data Using AI Who's it for Sales teams, marketers, and business development professionals who need to automatically enrich their CRM records with detailed company information from LinkedIn profiles. Perfect for anyone doing B2B outreach who wants to personalize their messaging at scale. What it does This workflow transforms bare-bones lead records into rich, personalized prospect profiles by: Automatically scraping LinkedIn company profiles Using AI (GPT-4) to extract key business intelligence Generating 15+ email-ready personalization variables Updating your CRM with structured, actionable data The workflow pulls company overviews, products/services, funding information, recent posts, and converts everything into natural-language variables that can be dropped directly into your outreach templates. How it works Trigger: Workflow starts when a new lead is added to Airtable (or on schedule) Fetch: Retrieves the lead record containing the LinkedIn company URL Scrape: Pulls the raw HTML from the company's LinkedIn profile Clean: Strips HTML tags and formats content for AI processing Analyze: GPT-4 extracts structured company intelligence (overview, products, market presence, recent posts) Transform: Converts analysis into 15+ email-ready variables with natural phrasing Update: Writes enriched data back to your CRM Setup Requirements Airtable account** (free tier works fine) OpenAI API key** (GPT-4o-mini recommended for cost-effectiveness) LinkedIn company URLs** stored in your CRM 5 minutes** for initial configuration How to set up Configure Airtable Connection Replace YOUR_AIRTABLE_BASE_ID with your base ID Replace YOUR_TABLE_ID with your leads table ID Ensure your table has a "LinkedIn Organization URL" field Add your Airtable API credentials Add OpenAI Credentials Click on both OpenAI nodes Add your OpenAI API key GPT-4o-mini is recommended (cost-effective and fast) Set Up Trigger Add a trigger node (Schedule, Webhook, or Airtable trigger) Configure to run when new leads are added or on a daily schedule Test the Workflow Add a test lead with a LinkedIn company URL Execute

🚀 Transform Your Job Hunt with AI-Powered Telegram Bot Turn job searching into a conversational experience! This intelligent Telegram bot automatically scrapes job postings from LinkedIn, Indeed, and Monster, filters for sales & marketing positions, and delivers personalized results directly to your chat. ✨ Key Features Interactive Telegram Commands**: Simple /jobs [keyword] [location] searches Multi-Platform Scraping**: Simultaneous data collection from 3 major job boards AI-Powered Filtering**: Smart relevance detection and experience level classification Real-Time Notifications**: Instant job alerts delivered to Telegram Automated Data Storage**: Saves results to Google Sheets and Airtable Duplicate Removal**: Advanced deduplication across platforms Mobile-First Experience**: Full job search functionality through Telegram 🎯 Perfect For Sales Professionals**: Account managers, sales representatives, business development Marketing Experts**: Digital marketers, marketing managers, growth specialists Recruiters**: Streamlined candidate sourcing and job market analysis Job Seekers**: Hands-free job discovery with instant notifications 🛠️ Setup Requirements Required Credentials: Telegram Bot Token**: Create bot via @BotFather Bright Data API**: Professional web scraping service (LinkedIn/Indeed datasets) Google Sheets OAuth2**: For spreadsheet integration Airtable Token**: Database storage and management Prerequisites: n8n instance with HTTPS enabled (required for Telegram webhooks) Valid domain name with SSL certificate Basic understanding of Telegram bot commands 🔧 How It Works User Experience: Send /start to activate the bot and see available commands Use /jobs sales manager New York to search for specific positions Receive formatted job results instantly in Telegram Click "Apply Now" links to go directly to job postings All jobs automatically saved to your connected spreadsheets Behind the Scenes: Command Processing: Bot parses user input for keywords and location Parallel Scraping: Simultaneous API calls to LinkedIn, Indeed, and Monster AI Processing: Intelligent filtering, experience level detection, remote work identification Data Enhancement: Salary extraction, duplicate removal, relevance scoring Multi-Format Storage: Automatic saving to Google Sheets, Airtable, and JSON export Real-Time Response: Formatted results delivered back to Telegram chat 🎨 Telegram Bot Commands /start - Welcome message and command overview /jobs [keyword] [location] - Search for jobs (e.g., /jobs marketing manager remote) /help - Show detailed help information /status - Check bot status and recent activity 📊 Sample Output The bot delivers beautifully formatted job results: 🎯 Job Search Results 🎯 Found 7 relevant opportunities Platforms: linkedin, indeed, monster Remote jobs: 3 ─────────────────── 💼 Senior Sales Manager 🏢 TechCorp Industries 📍 New York, NY 💰 $80,000 - $120,000 🌐 Remote Available 📊 senior level 🔗 Apply Now 🔒 Security & Best Practices Rate Limiting**: Built-in Telegram API compliance (30 requests/second) Error Handling**: Graceful failure recovery with user-friendly messages Input Validation**: Sanitized user input to prevent injection attacks Credential Management**: Secure API key storage using n8n credentials system HTTPS Enforcement**: Required for production Telegram webhook integration 📈 Benefits & ROI 95% Time Reduction**: Automated job discovery vs manual searching Multi-Source Coverage**: Access 3 major job platforms simultaneously Mobile Accessibility**: Search jobs anywhere using Telegram mobile app Real-Time Alerts**: Never miss new opportunities with instant notifications Data Organization**: Automatic spreadsheet management for job tracking Market Intelligence**: Comprehensive job market analysis and trends 🚀 Advanced Customization Custom Keywords**: Modify filtering logic for specific industries Location Targeting**: Adjust geographic search parameters Experience Levels**: Fine-tune senior/mid/entry level detection Additional Platforms**: Easily add more job boards via HTTP requests Notification Scheduling**: Set up periodic automated job alerts Team Integration**: Deploy for multiple users or team channels 💡 Use Cases Individual Job Seekers**: Personal job hunting assistant Recruitment Agencies**: Streamlined candidate sourcing Sales Teams**: Territory-specific opportunity monitoring Marketing Departments**: Industry trend analysis and competitor tracking Career Coaches**: Client job market research and opportunity identification Ready to revolutionize your job search? Deploy this workflow and start receiving personalized job opportunities directly in Telegram!

Overview Transform your accounts payable department with this enterprise-grade invoice processing solution. This workflow automates the entire invoice lifecycle - from document ingestion through payment processing. It handles invoices from multiple sources (Google Drive, email attachments, API submissions), extracts data using AI, validates against purchase orders, routes for appropriate approvals based on amount thresholds, and integrates seamlessly with your ERP system. The solution includes vendor master data management, duplicate invoice detection, real-time spend analytics, and complete audit trails for compliance. What You Can Do This comprehensive workflow creates an intelligent invoice processing pipeline that monitors multiple input channels (Google Drive, email, webhooks) for new invoices and automatically extracts data from PDFs, images, and scanned documents using AI. It validates vendor information against your master database, matches invoices to purchase orders, and detects discrepancies. The workflow implements multi-level approval routing based on invoice amount and department, prevents duplicate payments through intelligent matching algorithms, and integrates with QuickBooks, SAP, or other ERP systems. Additionally, it generates real-time dashboards showing processing metrics and cash flow insights while sending automated reminders for pending approvals. Who It's For Perfect for medium to large businesses, accounting departments, and financial service providers processing more than 100 invoices monthly across multiple vendors. Ideal for organizations that need to enforce approval hierarchies and spending limits, require integration with existing ERP/accounting systems, want to reduce processing time from days to minutes, need audit trails and compliance reporting, and seek to eliminate manual data entry errors and duplicate payments. The Problem It Solves Manual invoice processing creates significant operational challenges including data entry errors (3-5% error rate), processing delays (8-10 days per invoice), duplicate payments (0.1-0.5% of invoices), approval bottlenecks causing late fees, lack of visibility into pending invoices and cash commitments, and compliance issues from missing audit trails. This workflow reduces processing time by 80%, eliminates data entry errors, prevents duplicate payments, and provides complete visibility into your payables process. Setup Instructions Google Drive Setup: Create dedicated folders for invoice intake and configure access permissions PDF Vector Configuration: Set up API credentials with appropriate rate limits for your volume Database Setup: Deploy the provided schema for vendor master and invoice tracking tables Email Integration: Configure IMAP credentials for invoice email monitoring (optional) ERP Connection: Set up API access to your accounting system (QuickBooks, SAP, etc.) Approval Rules: Define approval thresholds and routing rules in the configuration node Notification Setup: Configure Slack/email for approval notifications and alerts Key Features Multi-Channel Invoice Ingestion**: Automatically collect invoices from Google Drive, email attachments, and API uploads Advanced OCR and AI Extraction**: Process any invoice format including handwritten notes and poor quality scans Vendor Master Integration**: Validate and enrich vendor data, maintaining a clean vendor database 3-Way Matching**: Automatically match invoices to purchase orders and goods receipts Dynamic Approval Routing**: Route based on amount, department, vendor, or custom rules Duplicate Detection**: Prevent duplicate payments using fuzzy matching algorithms Real-Time Analytics**: Track KPIs like processing time, approval delays, and early payment discounts Exception Handling**: Intelligent routing of problematic invoices for manual review Audit Trail**: Complete tracking of all actions, approvals, and system modifications Payment Scheduling**: Optimize payment timing to capture discounts and manage cash flow Customization Options This workflow can be customized to add industry-specific extraction fields, implement GL coding rules based on vendor or amount, create department-specific approval workflows, add currency conversion for international invoices, integrate with additional systems (banks, expense management), configure custom dashboards and reporting, set up vendor portals for invoice status inquiries, and implement machine learning for automatic GL coding suggestions. Note: This workflow uses the PDF Vector community node. Make sure to install it from the n8n community nodes collection before using this template.

This n8n workflow template automatically processes phone interview transcripts using AI to evaluate candidates against specific criteria and saves the results to Google Sheets. Perfect for HR departments, recruitment agencies, or any business conducting phone screenings. What This Workflow Does This automated workflow: Receives phone interview transcripts via webhook Uses OpenAI GPT models to analyze candidate responses against predefined qualification criteria Extracts key information (name, phone, location, qualification status) Automatically saves structured results to a Google Sheet for easy review and follow-up The workflow is specifically designed for driving job interviews but can be easily adapted for any position with custom evaluation criteria. Tools & Services Used N8N** - Workflow automation platform OpenAI API** - AI-powered transcript analysis (GPT-4o-mini) Google Sheets** - Data storage and management Webhook** - Receiving transcript data Prerequisites Before implementing this workflow, you'll need: N8N Instance - Self-hosted or cloud version OpenAI API Account - For AI transcript processing Google Account - For Google Sheets integration Phone Interview System - That can send webhooks (like Vapi.ai) Step-by-Step Setup Instructions Step 1: Set Up OpenAI API Access Visit OpenAI's API platform Create an account or log in Navigate to API Keys section Generate a new API key Copy and securely store your API key Step 2: Create Your Google Sheet Option 1: Use Our Pre-Made Template (Recommended) Copy our template: Driver Interview Results Template Click "File" → "Make a copy" to create your own version Rename it as desired Copy your new sheet's URL - you'll need this for the workflow Option 2: Create From Scratch Go to Google Sheets Create a new spreadsheet Name it "Driver Interview Results" (or your preferred name) Set up the following column headers in row 1: A1: name B1: phone C1: cityState D1: qualifies E1: reasoning Copy the Google Sheet URL - you'll need this for the workflow Step 3: Import and Configure the N8N Workflow Import the Workflow Copy the workflow JSON from the template In your N8N instance, go to Workflows → Import from JSON Paste the JSON and import Configure OpenAI Credentials Click on either "OpenAI Chat Model" node Set up credentials using your OpenAI API key Test the connection to ensure it works Configure Google Sheets Integration Click on the "Save to Google Sheets" node Set up Google Sheets OAuth2 credentials Select your spreadsheet from the dropdown Choose the correct sheet (usually "Sheet1") Update the Webhook Click on the "Webhook" node Note the webhook URL that n8n generates This URL will receive your transcript data Step 4: Customize Evaluation Criteria The workflow includes predefined criteria for a Massachusetts driving job. To customize for your needs: Click on the "Evaluate Candidate" node Modify the system message to include your specific requirements Update the evaluation criteria checklist Adjust the JSON output format if needed Current Evaluation Criteria: Valid Massachusetts driver's license No felony convictions Clean driving record (no recent tickets/accidents) Willing to complete background check Can pass drug test (including marijuana) Available full-time Monday-Friday Lives in Massachusetts Step 5: Connect to Vapi.ai (Phone Interview System) This workflow is specifically designed to work with Vapi.ai's phone interview system. Here's how to connect it: Setting Up the Vapi Integration Copy Your N8N Webhook URL In your n8n workflow, click on the "Webhook" node Copy the webhook URL (it should look like: https://your-n8n-instance.com/webhook-test/351ffe7c-69f2-4657-b593-c848d59205c0) Configure Your Vapi Assistant Log into your Vapi.ai dashboard Create or edit your phone interview assistant In the assistant settings, find the "Server" section Set the Server URL to your n8n webhook URL Set timeout to 20 seconds (as configured in the workflow) Configure Server Messages In your Vapi assistant settings, enable these server messages: end-of-call-report transcript[transcriptType="final"] Set Up the Interview Script Use the provided interview script in your Vapi assistant (found in the workflow's system message) This ensures consistent data collection for the AI evaluation Expected Data Format from Vapi The workflow expects Vapi to send data in this specific format: { "body": { "message": { "artifact": { "transcript": "AI: Hi. Are you interested in driving for Bank of Transport?\nUser: Yes.\nAI: Great. Before we go further..." } } } } Vapi Configuration Checklist ✅ Webhook URL set in Vapi assistant server settings ✅ Server messages enabled: end-of-call-report, transcript[transcriptType="final"] ✅ Interview script configured in assistant ✅ Assistant set to send webhooks on call completion Alternative Phone Systems If you're not using Vapi.ai, you can adapt this workflow for other phone systems by: Modifying the "Edit Fields2" node to extract transcripts from your system's data format Updating the webhook data structure expectations Ensuring your phone system sends the complete interview transcript Step 6: Test the Workflow Test with Sample Data Use the "Execute Workflow" button with test data Verify that data appears correctly in your Google Sheet Check that the AI evaluation logic works as expected End-to-End Testing Send a test webhook with a real transcript Monitor each step of the workflow Confirm the final result is saved to Google Sheets Workflow Node Breakdown Webhook - Receives transcript data from your phone system Edit Fields2 - Extracts the transcript from the incoming data Evaluate Candidate - AI analysis using GPT-4o-mini to assess qualification Convert to JSON - Ensures proper JSON formatting with structured output parser Save to Google Sheets - Automatically logs results to your spreadsheet Customization Options Modify Evaluation Criteria Edit the system prompt in the "Evaluate Candidate" node Add or remove qualification requirements Adjust the scoring logic Change Output Format Modify the JSON schema in the "Structured Output Parser" node Update Google Sheets column mapping accordingly Add Additional Processing Insert nodes for email notifications Add Slack/Discord alerts for qualified candidates Integrate with your CRM or ATS system Troubleshooting Common Issues: OpenAI API Errors**: Check API key validity and billing status Google Sheets Not Updating**: Verify OAuth permissions and sheet access Webhook Not Receiving Data**: Confirm URL and POST format from your phone system AI Evaluation Inconsistencies**: Refine the system prompt with more specific criteria Usage Tips Monitor Token Usage**: OpenAI charges per token, so monitor your usage Regular Review**: Periodically review AI evaluations for accuracy Backup Data**: Export Google Sheets data regularly for backup Privacy Compliance**: Ensure transcript handling complies with local privacy laws Need Help with Implementation? For professional setup, customization, or troubleshooting of this workflow, contact: Robert - Ynteractive Solutions Email**: rbreen@ynteractive.com Website**: www.ynteractive.com LinkedIn**: linkedin.com/in/robert-interactive Specializing in AI-powered workflow automation, business process optimization, and custom integration solutions.

This n8n template from Intuz provides a complete solution to automate your entire invoicing process. It intelligently syncs confirmed sales orders from your Airtable base to QuickBooks, automatically creating new customers if they don't exist before generating a perfectly matched invoice. It then logs all invoice details back into Airtable, creating a flawless, end-to-end financial workflow. Use Cases 1. Accounting & Finance Teams: Automatically generate QuickBooks invoices from new orders confirmed in Airtable. Keep all invoices and customer details synced across systems in real time. 2. Sales & Operations Teams: Track order status and billing progress directly from Airtable without switching platforms. Ensure every confirmed sale automatically triggers an invoice in QuickBooks. 3. Business Owners / Admins: Eliminate double-entry between Airtable and QuickBooks. Maintain accurate, audit-ready financial records with minimal effort. How it works 1. Trigger from Airtable: The workflow starts instantly when a sales order is ready to be invoiced in your Airtable base (triggered via a webhook). 2. Check for Customer in QuickBooks: It searches your QuickBooks account to see if the customer from the sales order already exists. 3. Create New Customer (If Needed): If the customer is not found, it automatically creates a new customer record in QuickBooks using the details from your Airtable Customers table. 4. Create QuickBooks Invoice: Using the correct customer record (either existing or newly created), it gathers all order line items from Airtable and generates a detailed invoice in QuickBooks. 5. Log Invoice Back to Airtable: After the invoice is successfully created, the workflow updates your Airtable base by adding a new record to your Invoices & Payments table and updating the original Confirmed Orders record with the new QuickBooks Invoice ID, marking it as synced. Key Requirements to Use This Template 1. n8n Instance: An active n8n account (Cloud or self-hosted). 2. Airtable Base: An Airtable base on a "Pro" plan or higher with tables for Confirmed Orders, Customers, Order Lines, Product & Service, and Invoices & Payments. Field names must match those in the setup guide. 3. QuickBooks Online Account: An active QuickBooks Online account with API access. Step-by-Step Setup Instructions Step 1: Import and Configure the n8n Workflow Import Workflow:** In n8n, import the Client-Quickbook-Invoices-via-AirTable.json file. Get Webhook URL:** Click on the first node, "Webhook". Copy the "Test URL". Keep this n8n tab open. Configure Airtable Nodes:** There are six Airtable nodes. For each one, connect your Airtable credentials and select the correct Base and Table. Configure QuickBooks Nodes:** There are four QuickBooks-related nodes. For each one, connect your QuickBooks Online credentials. CRITICAL:** Click on the "Create Invoice URL" (HTTP Request) node. You must edit the URL and replace the placeholder number (9341455145770046) with your own QuickBooks Company ID. (Find this in your QuickBooks account settings under "Billing & Subscription"). Save and Activate**: Click "Save", then toggle the workflow to "Active". After activating, copy the new "Production URL" from the Webhook node. Customization Guide You can adapt this template for various workflows by tweaking a few nodes: Use a different Airtable Base:** Update the Base ID and Table ID in all Airtable nodes (Get Orders Records, Get Customer Details, Get Products, etc.). Switch from Sandbox to Live QuickBooks:** Replace the Sandbox company ID and endpoint in the “Create Invoice URL” node with your production QuickBooks company ID. Add more invoice details:** Edit the Code and Parse in HTTP nodes to include additional fields (like Tax, Shipping, or Notes). Support multiple currencies:** Add a “Currency” field mapping in both Airtable and QuickBooks nodes. Connect with us Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Workflow Automation Click here- Get Started

Who this is for This workflow is designed for: Automation engineers building AI-powered data pipelines Product managers & analysts needing structured insights from web pages Researchers & content teams extracting summaries from documentation or articles HR, compliance, and knowledge teams converting unstructured web content into structured records n8n self-hosted users leveraging advanced scraping and LLM enrichment It is ideal for anyone who wants to transform any public URL into structured data + clean summaries automatically. What problem this workflow solves Web content is often unstructured, verbose, and inconsistent, making it difficult to: Extract structured fields reliably Generate consistent summaries Reuse data across spreadsheets, dashboards, or databases Eliminate manual copy-paste and interpretation This workflow solves the problem of turning arbitrary web pages into machine-readable JSON and human-readable summaries, without custom scrapers or manual parsing logic. What this workflow does The workflow integrates Decodo, Google Gemini, and Google Sheets to perform automated extraction of structured data. Here’s how it works step-by-step: Input Setup The workflow begins when the user executes it manually or passes a valid URL. The input includes url. Profile Extraction with Decodo Accepts any valid URL as input Scrapes the page content using Decodo Uses Google Gemini to: Extract structured data in JSON format Generate a concise, factual summary Cleans and parses AI-generated JSON safely Merges structured data and summary output Stores the final result in Google Sheets for reporting or downstream automation JSON Parsing & Merging The Code Node cleans and parses the JSON output from the AI for reliable downstream use. The Merge Node combines both structured data and the AI-generated summary. Data Storage in Google Sheets The Google Sheets Node appends or updates the record, storing the structured JSON and summary into a connected spreadsheet. End Output A unified, machine-readable data in JSON + an executive-level summary suitable data analysis or downstream automation. Setup Instructions Prerequisites n8n account** with workflow editor access Decodo API credentials** - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard Google Gemini (PaLM) API access** Google Sheets OAuth credentials** Setup Steps Import the workflow into your n8n instance. Configure Credentials Add your Decodo API credentials in the Decodo node. Connect your Google Gemini (PaLM) credentials for both AI nodes. Authenticate your Google Sheets account. Edit Input Node In the Set the Input Fields node, replace the default URL with your desired profile or dynamic data source. Run the Workflow Trigger manually or via webhook integration for automation. Verify that structured profile data and summary are written to the linked Google Sheet. How to customize this workflow to your needs You can easily extend or adapt this workflow: Modify Structured Output Change the Gemini extraction prompt to match your own JSON schema Add required fields such as authors, dates, entities, or metadata Improve Summarization Adjust summary length or tone (technical, executive, simplified) Add multi-language summarization using Gemini Change Output Destination Replace Google Sheets with: Databases (Postgres, MySQL) Notion Slack / Email File storage (JSON, CSV) Add Validation or Filtering Insert IF nodes to: Reject incomplete data Detect errors or hallucinated output Trigger alerts for malformed JSON Scale the Workflow Replace manual trigger with: Webhook Scheduled trigger Batch URL processing Summary This workflow provides a powerful, generic solution for converting unstructured web pages into structured, AI-enriched datasets. By combining Decodo for scraping, Google Gemini for intelligence, and Google Sheets for persistence, it enables repeatable, scalable, and production-ready data extraction without custom scrapers or brittle parsing logic.