Workflow Templates

Workflow Overview This workflow automatically fetches the latest "Ask HN: Who is hiring?" posts from Hacker News, extracts individual job listings, cleans the raw text, converts them into structured job listings using Google Gemini AI, and saves them into Airtable. Components It’s a full end-to-end automation system combining: Algolia API** for HN data Text cleaning** Gemini AI (via LangChain)** for parsing job descriptions Structured JSON extraction** Airtable integration** to store the final data 🎯 Use Cases Automatically build a job board from HN posts Track startup hiring trends Feed remote job alerts into a CRM or Slack Enrich a hiring intelligence database 🔧 Nodes & Services Used HTTP Request (Algolia + Firebase API) SplitOut, Set, Filter, Function, Limit Google Gemini (via LangChain integration) Output Parser Structured Airtable (API token required) 📌 Credentials Required Google Gemini (PaLM/Gemini API) Airtable Personal Access Token Algolia Application ID & API Key (via Header Auth) 📦 Tags hacker-news, jobs, airtable, ai, gemini, automation, hn, langchain, workflow Screenshots

This n8n template from Intuz delivers a complete and automated solution to streamline your development workflow for a single repository. By embedding specific keywords and a JIRA issue ID within your git commit commands, this workflow automatically creates a Pull Request in GitHub and simultaneously updates the corresponding JIRA ticket. This provides a complete, seamless integration that eliminates manual steps and keeps your project management perfectly in sync with your codebase. How it works This workflow acts as a powerful bridge between your Git repository and your project management tools, driven entirely by the structure of your commit messages. GitHub Webhook Trigger: The workflow starts when a developer pushes a new commit to a specified repository in GitHub. Parse Commit Message: A Code node extracts key information from the commit message: The JIRA Issue Key (e.g., FF-1196). The base branch for the PR (e.g., development). Action commands like [auto-pr] and [taskcompleted]. Conditional PR Creation: An IF node checks if the [auto-pr] command is present. If yes, it uses the GitHub node to automatically create a pull request from the developer's branch to the specified base branch. If no, this step is skipped, allowing for multiple commits before a PR is made. Conditional JIRA Update: Another IF node checks for the [taskcompleted] command. If yes, it uses the JIRA node to transition the corresponding issue to your "Done" status (e.g., "Task Completed" or "In Review"). If no, the JIRA issue remains in its current state, perfect for work-in-progress commits. How to Use: Quick Start Guide Click the "Use Template" button to import this workflow into your n8n instance. Configure the GitHub Trigger: Open the "GitHub Push Trigger" node. It will display a unique Webhook URL. Copy this URL. In your GitHub repository, go to Settings > Webhooks > Add webhook. Paste the URL into the Payload URL field. Set the Content type to application/json. Under "Which events would you like to trigger this webhook?", select Just the push event. Click Add webhook. Connect Your Accounts: GitHub: Select your GitHub API credential in the "Create Pull Request" node. JIRA : Select your JIRA API credential in the "Update JIRA Issue Status" node. Customize the JIRA Transition (Important): Open the "Update JIRA Issue Status" node. In the Transition parameter, you need to set the specific status you want to move the issue to (e.g., 'Done', 'Completed', 'In Review'). You can use the ID or the exact name of the transition from your JIRA project's workflow. Activate the Workflow: Save your changes and activate the workflow. You're ready to automate! Example Commit Message: git commit -m "FF-1196 Implement OAuth login [auto-pr,development,taskcompleted]" Key Requirements to Use Template An active n8n instance. A GitHub account with repository admin permissions to create webhooks. A JIRA Cloud account with permissions to update issues. Developers who can follow the specified git commit message format. 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 Worflow Automation Click here- Get Started

Overview Transform your contract management process with this enterprise-grade workflow that handles the complete contract lifecycle - from initial intake through execution, monitoring, and renewal. This comprehensive solution combines AI-powered contract analysis with automated risk scoring, clause comparison, obligation tracking, and proactive alerts. It integrates with multiple data sources including email, SharePoint, contract CLM systems, and creates a centralized contract intelligence hub that prevents revenue leakage, ensures compliance, and accelerates deal velocity. What You Can Do This advanced workflow orchestrates a complete contract management ecosystem that monitors multiple channels (email, Google Drive, SharePoint, APIs) for new contracts and amendments. It extracts and analyzes over 50 contract data points using AI, performs multi-dimensional risk assessment across legal, financial, and operational factors, compares clauses against your approved template library, tracks all obligations and key dates with automated reminders, integrates with Salesforce/CRM for deal alignment, routes contracts through dynamic approval workflows based on risk scores, generates executive dashboards with contract analytics, and maintains a searchable repository with version control. The system handles complex scenarios including multi-party agreements, framework contracts with statements of work, international contracts requiring jurisdiction analysis, and M&A due diligence requiring bulk contract review. Who It's For Designed for enterprise legal operations teams managing thousands of contracts annually, procurement departments negotiating complex vendor agreements, contract managers overseeing multi-million dollar portfolios, compliance teams ensuring regulatory adherence across jurisdictions, sales operations needing faster contract turnaround, and C-suite executives requiring contract intelligence for strategic decisions. Essential for organizations in regulated industries (healthcare, finance, government) and companies undergoing digital transformation of their legal operations. The Problem It Solves Manual contract management creates massive operational risks and inefficiencies. Organizations typically have contracts scattered across emails, shared drives, and filing cabinets with no central visibility. This leads to missed renewal deadlines costing 5-10% of contract value, unauthorized contract variations creating compliance risks, obligation failures resulting in penalties and damaged relationships, and inability to leverage favorable terms across similar contracts. Studies show that inefficient contract management costs organizations up to 9% of annual revenue. This workflow creates a single source of truth for all contracts, automates tracking and compliance, and provides predictive insights to prevent issues before they occur. Setup Instructions Multi-Channel Integration: Configure connectors for email (Office 365/Gmail), Google Drive, SharePoint, and contract management systems PDF Vector Setup: Install PDF Vector node and configure API with enterprise rate limits Database Configuration: Set up PostgreSQL/MySQL for contract repository with proper indexing Template Library: Upload your standard contract templates and approved clause library Risk Framework: Configure risk scoring matrix for your industry (legal, financial, operational risks) Approval Matrix: Define approval routing based on contract value, type, and risk score CRM Integration: Connect to Salesforce/HubSpot for opportunity and account alignment Notification Setup: Configure Slack/Teams channels and email distribution lists Dashboard Creation: Set up Tableau/PowerBI connectors for executive reporting Security Configuration: Enable encryption, audit logging, and role-based access controls Key Features Intelligent Intake System**: Monitor email attachments, shared folders, CRM uploads, and API submissions Advanced AI Extraction**: Extract 50+ data points including nested obligations and conditional terms Multi-Dimensional Risk Scoring**: Analyze legal, financial, operational, and reputational risks Clause Library Comparison**: Compare against approved templates and flag deviations Obligation Management**: Track deliverables, milestones, and SLAs with automated alerts Dynamic Approval Routing**: Route based on AI risk score, contract value, and deviation analysis Version Control & Redlining**: Track all changes and maintain complete audit trail Salesforce Integration**: Sync contract data with opportunities and accounts Predictive Analytics**: Forecast renewal likelihood and negotiation outcomes Bulk Processing**: Handle M&A due diligence with parallel processing of hundreds of contracts Multi-Language Support**: Process contracts in 15+ languages with automatic translation Executive Dashboards**: Real-time visibility into contract portfolio and risk exposure Customization Options Implement industry-specific modules for healthcare (BAAs, DPAs), financial services (ISDAs, loan agreements), technology (SaaS, licensing), or government contracting. Add AI models trained on your historical contracts for better extraction accuracy. Create custom risk factors for emerging regulations like AI governance or ESG compliance. Build integration with specific CLM systems (Ironclad, Docusign CLM, Icertis). Implement advanced analytics including contract similarity scoring, win-rate analysis by clause variations, and automatic playbook generation. Add blockchain integration for smart contract execution and configure automated contract assembly for standard agreements. Note: This workflow uses the PDF Vector community node. Make sure to install it from the n8n community nodes collection before using this template.

🤖AI-Powered Appointment Scheduling with Google Calendar & Sheets Virtual Receptionist Automate customer conversations with an AI-powered virtual receptionist. This workflow can chat naturally with clients, answer general business questions (like services, location, and hours), check availability in Google Calendar, book appointments, and save customer details in Google Sheets. Fully customizable for any business type — salons, clinics, agencies, consultants, and more. 📖 How It Works Welcome the customer when the customer says hi AI greets warmly: “Hello! I’m [AI name] from [Business name].” Answer general questions Provides instant replies about services, pricing, business location, hours, and availability. Understand their need Identifies the service requested and preferred time. Check availability Queries Google Calendar for open slots. Gather customer details Collects name, phone, and email (optional). Confirm booking Creates the appointment in Google Calendar. Save records Logs booking and customer info into Google Sheets. ⚙️ Setup Steps (Quick) Connect your Google Calendar and Google Sheets accounts. Add your business details (name, type, services, hours, policies) to the Business Info Sheet. Configure your OpenAI API key (or use n8n free credits). Optional: Connect Twilio WhatsApp for direct chat responses. 🏢 Example Business Info (Google Sheet) | business_id | business_name | business_type | location | phone | email | services | calendar_id | timezone | currency | working_hours | ai_name | ai_personality | ai_role | emergency_available | booking_advance_days | cancellation_hours | |-------------|-----------------|---------------------|----------------------------------|-----------------|---------------------------|----------|-----------------------|----------|----------|--------------------------------|---------|-----------------------------------|------------------------------------------------------------------------------------------------|----------------------|----------------------|-------------------| |001| Luxe Hair Studio | Hair & Beauty Salon | 123 Main Street, New York, NY 10001 | 1 (XXX) XXX-XXXX | yourbusiness@email.com | “Haircut & Styling (60 minutes, $3500…)Hair Coloring (120 minutes, $8000…)…” | calendar-id-here | GMT -3 | USD | Mon–Sat: 9:00 AM – 7:00 PM, Sun: Closed | bella | Friendly, Stylish, Professional | Manages bookings, answers FAQs, recommends services, gives beauty tips, sends reminders, etc. | no | 10 | 24 | ✅ Purpose: Supplies context (services, pricing, hours, AI personality, booking policies). 💡 The AI uses this sheet to answer general business questions (e.g., “Where are you located?”, “Do you do hair colouring?”, “What are your working hours?”). 📊 Appointments Sheet Example | client_number | client_name | event_id | summary | services | |----------------|-------------|-----------|----------------------------------|----------| | 001 | Sarah Lee | evt-10293 | Appointment with Sarah Lee – Haircut & Styling | Haircut & Styling | | 002 | John Smith | evt-10294 | Appointment with John Smith – Highlights | Highlights | ✅ Purpose: Logs confirmed bookings with service details and links back to Google Calendar. 💡 Features ✅ AI receptionist with conversation memory ✅ Answers FAQs – location, services, hours, pricing ✅ Google Calendar integration for real-time availability ✅ Google Sheets integration for customer records & reporting ✅ Customizable AI name, role, and personality 🔑 Who It’s For Salons & Spas** – Manage bookings and FAQs Clinics & Health Services** – Automated scheduling + patient info Agencies & Consultants** – Answer inquiries + schedule meetings Any Service Business** – Save time, improve customer experience

How it works This template is an end-to-end demo of a chatbot using business data from multiple sources (e.g. Notion, Chargebee, Hubspot etc.) with RAG + SQL. Peliqan.io is used as a "cache" of all business data. Peliqan uses one-click ELT to sync all your business data to its built-in data warehouse, allowing for fast & accurate RAG and "Text to SQL" queries. The workflow will write source data to Supabase as a vector store, for RAG searches by the chatbot. The source URL (e.g. the URL of a Notion page) is added in metadata. The AI Agent will decide for each question to use either RAG or Text-to-SQL or a combination of both. Text-to-SQL is performed via the Peliqan node, added as a tool to the AI Agent. The question of the user in natural language is converted to an SQL query by the AI Agent. The query is executed by Peliqan.io on the source data and the result is interpreted by the AI Agent. RAG is typically used to answer knowledge questions, often on non-structured data (Notion pages, Google Drive etc.). Text-to-SQL is typically used to answer analytical questions, for example "Show list of customers with number of open support tickets and add customer revenue based on invoiced amounts". Preconditions You signed up for a Peliqan.io free trial account You have one or more data sources, e.g. a CRM, ERP, Accounting software, files, Notion, Google Drive etc. Set up steps Sign up for a free trial on peliqan.io: https://peliqan.io Add one or more sources in Peliqan (e.g. Hubspot, Pipedrive...) Copy your Peliqan API key under settings and use it here to add a Peliqan connection Run the "RAG" workflow to feed Supabase, change the name of the table in the Peliqan node "Get table data". Update the list of tables & columns that can be used for SQL in the System Message of the AI Agent. Visit https://peliqan.io/n8n for more information. Disclaimer: This template contains a community node and therefore only works for n8n self-hosted users.

Description: Overview This workflow generates automated revenue and expense comparison reports from a structured Google Sheet. It enables users to compare financial data across the current period, last month, and last year, then uses an AI agent to analyze and summarize the results for business reporting. Prerequisites A connected Google Sheets OAuth2 credential. A valid DeepSeek AI API (or replaceable with another Chat Model). A sub-workflow (child workflow) that handles processing logic. Properly structured Google Sheets data (see below). Required Google Sheet Structure Column headers must include at least: Date, Amount, Type. Setup Steps Import the workflow into your n8n instance. Connect your Google Sheets and DeepSeek API credentials. Update: Sheet ID and Tab Name (already embedded in node: Get revenual from google sheet). Custom sub-workflow ID (in the Call n8n Workflow Tool node). Optionally configure chatbot webhook in the When chat message received node. What the Workflow Does Accepts date inputs via AI chat interface (ChatTrigger + AI Agent). Fetches raw transaction data from Google Sheets. Segments and pivots revenue by classification for: Current period Last month Last year Aggregates totals and applies custom titles for comparison. Merges all summaries into a final unified JSON report. Customization Options Replace DeepSeek with OpenAI or other LLMs. Change the date fields or cycle comparisons (e.g., quarterly, weekly). Add more AI analysis steps such as sentiment scoring or forecasting. Modify the pivot logic to suit specific KPI tags or labels. Troubleshooting Tips If Google Sheets fetch fails: ensure the document is shared with your n8n Google credential. If parsing errors: verify that all dates follow the expected format. Sub-workflow must be active and configured to accept the correct inputs (6 dates). SEO Keywords (ẩn hoặc mô tả ngầm): Google Sheets report, AI financial report, compare revenue by month, expense analysis automation, chatbot n8n report generator, n8n Google Sheet integration

WhatsApp customer service bot (with voice note transcription) handling FAQ, service enquiries and schedule appointments Who’s it for This template is designed for businesses that provide customer support and appointment-based services over WhatsApp. It’s ideal for service providers (e.g., clinics, salons, repair shops, consultants) that want to automate FAQs, share service information, handle voice note inquiries, and schedule appointments without manual effort. How it works / What it does This workflow creates a WhatsApp customer service assistant that: Transcribes voice notes** sent by customers into text for further processing. Answers customer FAQs by looking up a Google Sheet knowledge base. Provides service information (name, description, price) from a Google Sheet. Schedules appointments by: Asking the customer which service they want. Collecting their preferred day and time. Checking Google Calendar for available slots. Offering 3 options and letting the customer choose. Collecting name, email, and phone number. Creating the confirmed appointment in Google Calendar. Sends all customer-facing messages via a WhatsApp integration node. How to set up Connect your tools Link your Google Sheets for FAQs and Services. Connect your Google Calendar account. Configure your WhatsApp integration. Connect a transcription service (e.g., Whisper, Google Speech-to-Text, or another transcription API). Prepare your data FAQs Google Sheet → must contain columns: id | question | answer Services Google Sheet → must contain columns: id | service_name | service_description | price Adjust the flow Update the service names and questions to match your business. Set the correct time zone in the Google Calendar node. Update the WhatsApp integration node with your business account. Configure the transcription node with your chosen API credentials. Requirements Google Sheets (for FAQs and Services) Google Calendar WhatsApp integration in n8n Speech-to-Text API (for transcribing voice notes) How to customize the workflow Adding new FAQs**: Update the Google Sheet with new rows. Changing services**: Modify the Services Google Sheet to reflect updated offerings or prices. Custom messages**: Update the agent_reply node text to reflect your brand tone. Advanced logic**: Add routing for voice-note-only customers, VIP handling, or multilingual support. Notes This template uses multiple external integrations (Google Sheets, Google Calendar, WhatsApp, Speech-to-Text).

Quick Overview What it is: An n8n workflow that enables AI-first WhatsApp support with seamless human handoff. Why it’s unique: The AI agent answers queries using RAG (Supabase vector store + Gemini). If a human intervenes, the AI steps down. If there’s no human reply within 2 hours, the AI resumes. Channel constraints: Respects WhatsApp’s 24-hour customer care window and requires approved message templates for out-of-window messages. How It Works AI-first: Incoming WhatsApp messages are routed to an AI agent (Gemini) with knowledge grounded by a Supabase vector store. Human-in-the-loop: When a human responds in the dashboard, AI pauses for 2 hours for that conversation. Auto-resume: If no human reply within 2 hours, AI automatically resumes. Compliance: Only responds within 24 hours of the user’s last message, or via approved templates when outside this window. Architecture (At a Glance) Transport: Twilio WhatsApp; n8n http node. RAG: Supabase (Postgres + embeddings) stores knowledgebase. LLM: Google Gemini (free API key supported). Handoff: Human dashboard (GitHub project) logs and labels AI vs Human responses, and controls AI pause/resume. Prerequisites n8n (self-hosted or cloud) with public webhook access. Twilio account with a WhatsApp-enabled number. Supabase project for vector store. Google Gemini API key. Human dashboard: https://github.com/shadrack-ago/whatsapp-dashboard.git Setup Steps (n8n + Integrations) Import workflow in n8n Create new workflow → Import from JSON → Paste the provided JSON. Enable the workflow. Create credentials Twilio: Add TWILIO_ACCOUNT_SID, TWILIO_AUTH_TOKEN, TWILIO_PHONE_NUMBER. Do NOT paste real secrets publicly. Gemini: Add GEMINI_API_KEY. Supabase: Add SUPABASE_URL, SUPABASE_ANON_KEY (or service role where needed), and your table/bucket names. Connect Twilio WhatsApp WhatsApp Business setup in Twilio, or Sandbox for testing. Point Twilio incoming webhook to your n8n webhook URL. Ensure approved templates for any out-of-window messaging. Set environment variables (examples) TWILIO_ACCOUNT_SID=... TWILIO_AUTH_TOKEN=... TWILIO_PHONE_NUMBER=+1... GEMINI_API_KEY=... SUPABASE_URL=... SUPABASE_ANON_KEY=... SUPABASE_TABLE=knowledge_base EMBEDDING_MODEL HUMAN_TIMEOUT_MS=7200000 (2 hours) Human-in-the-loop dashboard Follow the repo guide: https://github.com/shadrack-ago/whatsapp-dashboard.git Run the dashboard and connect it to the same conversation store used by the workflow. Verify that human responses are captured and labeled; confirm AI pause/resume logic. Supabase for RAG Create table(s) for documents and embeddings. Ingest content per this tutorial:Supabase Tutorial Confirm your n8n nodes query the vector store before calling Gemini. Gemini setup Get API key: Gemini API Set model (e.g., gemini-pro or latest available in your environment). Test Send a WhatsApp message to your Twilio number. Observe AI response. Trigger a human reply via the dashboard → confirm AI pauses for that thread. Wait 2 hours or adjust HUMAN_TIMEOUT_MS to test auto-resume. Customization Providers: You can swap Twilio for Meta’s WhatsApp Cloud API; keep the 24-hour and template rules. Tone/Policies: Adjust system prompts and fallback behaviors in the LLM node. RAG Quality: Tune chunking, TOP_K, and embedding model for better retrieval. Timeouts: Change HUMAN_TIMEOUT_MS to alter handoff duration. WhatsApp Policy Notes 24-hour window: Replies must occur within 24 hours of user’s last message; otherwise use an approved template. Templates: Create and get approval inside Twilio/Meta before sending out-of-window messages. Security & Reliability Secrets: Store all keys in n8n credentials or environment variables. Never commit secrets to repos. Logging: Use the dashboard to audit AI vs Human messages. Rate limits: Add retry/backoff nodes for Twilio and LLM calls. Troubleshooting No replies: Check Twilio webhook URL and n8n workflow is active. Policy blocks: Ensure template use outside 24-hour window. Poor answers: Improve RAG data, increase TOP_K, refine prompts. Handoff not pausing: Verify dashboard is writing the “human active” flag that the workflow reads. Links Human dashboard (Full guide): GitHub Repo Link

📸🍽️ Telegram Food Photo → 🤖 Gemini Vision AI → 📊 Nutrition Data → 📄 Google Sheets + 🗂️ Drive What this workflow does 📸 Snap and send a photo of your meal via Telegram 🧠 Gemini Vision AI analyzes the image and estimates calories, protein, carbs, and fats 🤖 AI Agent structures the data with meal name, description, and timestamp 📄 Auto-logs nutrition data to Google Sheets for tracking 🗂️ Saves original meal photos to Google Drive with timestamped filenames 💬 Sends instant Telegram reply with full nutrition breakdown Why it's useful ⚡ Track nutrition in seconds—no manual entry or food databases 📊 Build a complete meal history with photos and macros in one place 🎯 AI estimates portion sizes and hidden ingredients (oils, sauces) 🏋️ Perfect for fitness tracking, meal prep, or health monitoring 📱 Works entirely through Telegram—no extra apps needed How it works 📲 Telegram Trigger → receives meal photo 🗂️ Google Drive → saves image with timestamp 🔎 Gemini Vision → analyzes food, estimates portions and macros 🤖 AI Agent → structures output (meal name, calories, protein, carbs, fats) 📄 Google Sheets → appends row with all nutrition data 💬 Telegram Reply → confirms with full breakdown What you'll need 🤖 Telegram Bot token 🧠 Google Gemini API key (includes Vision capabilities) 🔐 Google OAuth for Sheets + Drive 📊 Google Sheet with columns: Meal_Name, Date, Meal_description, Calories, Proteins, Carbs, Fats Setup steps 🔗 Connect credentials: Telegram, Google Gemini, Google Sheets, Google Drive 📄 Create Google Sheet with nutrition columns (see format above) 🗂️ Create Google Drive folder for meal photos 🧭 Update sheet ID and Drive folder ID in workflow 🧪 Test: send a meal photo via Telegram and check Sheet + Drive Customization ideas 📈 Daily summary: add scheduled workflow to calculate daily totals 🎯 Goal tracking: set IF conditions to alert when over/under calorie targets 📊 Charts: connect to Data Studio/Looker for visual progress tracking 🏃 Fitness integration: sync with MyFitnessPal or fitness apps Who it's for 🏋️ Fitness enthusiasts tracking macros without manual logging 🥗 Meal preppers analyzing portion sizes and nutrition 💪 Athletes monitoring calorie and protein intake 🩺 Health-conscious individuals building meal history 👨‍🍳 Nutritionists collecting client food data Quick Setup Guide - Before You Start - What You Need: 🔗 Telegram Bot (create via @BotFather) 🧠 Google Gemini API key with Vision enabled (get it here) 🔐 Google account for Sheets and Drive access 📊 Basic spreadsheet to track your meals Want help customizing? 📧 anirpoke@gmail.com 🔗 LinkedIn

Who’s it for This template is ideal for IT support teams, internal helpdesk automation engineers, and developers building intelligent ticketing systems. It helps streamline ITSM workflows by automatically classifying user queries, retrieving relevant knowledge base entries, and triggering incident creation in ServiceNow. How it works / What it does This workflow uses Google Gemini and Qdrant to power an intelligent ITSM assistant. When a user submits a query via chat: The Text Classifier categorizes the input as an Incident, Request, or Other. Based on the category: Incidents are automatically logged in ServiceNow. Requests trigger an HTTP call (e.g., for provisioning or access). Other queries are routed to an AI Agent that searches the FAQBase in Qdrant and responds contextually. The Gemini LLM enriches responses and summaries. The Qdrant Vector Store retrieves semantically similar answers from a pre-embedded FAQ knowledge base. The Summarization Chain condenses incident details for better tracking. Sticky notes are used throughout the workflow to document each node’s purpose and improve maintainability. How to set up Connect your Google Gemini API, Qdrant, and ServiceNow credentials. Populate the FAQBase collection in Qdrant with your ITSM knowledge base. Deploy the webhook to receive chat inputs. Test the flow using the Manual Trigger node. Customize the classifier categories and Gemini prompts as needed. Requirements Google Gemini API access Qdrant vector database with embedded FAQ data ServiceNow account with API access n8n instance with LangChain nodes installed How to customize the workflow Modify the Text Classifier categories to suit your organization’s ticket types. Add more FAQ entries to Qdrant for broader coverage. Replace the HTTP Request node with integrations relevant to your ITSM tools. Adjust the Gemini prompts to reflect your tone and support style. Extend the workflow with Slack, Teams, or email notifications for ticket updates.

Who is this for? This workflow is designed for software teams, project managers, and developers who manage work across Azure DevOps and GitHub. It helps organizations that use Azure DevOps for work item tracking but rely on GitHub for issue management and collaboration. If you need to ensure that your DevOps Stories and Tasks are mirrored in GitHub issues while keeping a single source of truth in Google Sheets, this workflow is for you. What problem is this workflow solving? / Use case Managing projects across multiple platforms often leads to missed updates and poor traceability. Stories created in Azure DevOps may not be tracked properly in GitHub.\ Tasks under Stories often lose visibility when teams split between platforms.\ Manual syncing between tools takes time and causes human errors. This workflow solves that problem by automating the sync between Azure DevOps Stories and GitHub Issues, while also keeping a Google Sheets record for cross-referencing and reporting. What this workflow does Triggers from Azure DevOps Stories -- When a Story is created or updated, the workflow is activated.\ Creates a GitHub Issue -- A new issue is generated in the specified GitHub repository.\ Assigns a random collaborator -- One repository collaborator is randomly assigned to the issue.\ Logs mapping in Google Sheets -- The Azure DevOps Story ID, GitHub Issue number, and URL are stored for tracking.\ Triggers from Azure DevOps Tasks -- When a Task linked to a Story is created, the workflow looks up its parent in Google Sheets.\ Updates the GitHub Issue -- The parent GitHub Issue is updated with a clickable link to the new Task for better visibility. Setup Connect your accounts GitHub (OAuth2 or personal token)\ Google Sheets (OAuth2)\ Azure DevOps (Webhook integration) Configure Webhooks Add the workflow's webhook URLs to Azure DevOps service hooks for Work Item Created/Updated events. Update repository details Set the GitHub repository where issues should be created. Customize Sheets Use the provided Google Sheet or link your own for issue mappings. How to customize this workflow to your needs Modify assignment logic**: Instead of random collaborator assignment, edit the Code node to assign issues based on workload or labels.\ Change Sheet schema**: Add more fields (e.g., State, IterationPath) to your Google Sheet for richer reporting.\ Expand task linking**: Customize the way Tasks are appended to GitHub issues (e.g., group by state, show due dates). Powered By Concept Recall https://conceptrecall.com

Who this is for This workflow is designed for researchers, marketing teams, customer success managers, and survey analysts who want to automatically generate AI-powered summaries of form responses collected via Jotform — turning raw feedback into actionable insights. It is ideal for: Teams conducting market research or post-event surveys. Customer experience teams that collect feedback via forms and need instant, digestible summaries. Product managers seeking concise overviews of user comments and suggestions. Analysts who want to compare comprehensive vs. abstract summaries for richer intelligence. What problem this workflow solves Analyzing open-ended Jotform responses manually can be slow, repetitive, and error-prone. This workflow automates the process by generating two AI summaries for every response: Comprehensive Summary — captures all factual details from the response. Abstract Summary — rephrases and synthesizes insights at a higher, conceptual level. With this workflow: Each response is summarized instantly using Google Gemini AI. Both comprehensive and abstract summaries are automatically generated and stored. Data is persisted in Google Sheets, DataTable, and Google Docs for further use. What this workflow does This n8n workflow transforms Jotform submissions into structured summaries using Google Gemini. Step-by-Step Breakdown Webhook Trigger (Jotform Integration) Listens for new Jotform submissions using the Webhook node. Receives full form data via the Webhook response. Set the Input Fields Extracts and assigns key fields like: FormTitle SubmissionID Body (the formatted form data) Prepares structured JSON to feed into the AI summarization stage. Comprehensive & Abstract Summarizer Powered by Google Gemini Chat Model (models/gemini-2.0-flash-exp). Custom prompt: You are an expert comprehensive summarizer. Build a detailed and abstract summary of the following {{ $json.body.pretty }}. Produces two distinct summaries: comprehensive_summary abstract_summary Structured Output Parser Ensures Gemini output matches a defined JSON schema: { "comprehensive_summary": "", "abstract_summary": "" } Guarantees reliable downstream integration with Sheets and Docs. Persist on DataTable Saves both summaries into an n8n DataTable for historical tracking or visualization. Useful for teams running internal analytics within n8n Cloud or self-hosted environments. Append or Update Row in Google Sheets Writes both summaries into a connected Google Sheet. Columns: comprehensive_summary abstract_summary Create Google Document Automatically generates a Google Docs file titled: {FormTitle}-{SubmissionID} Acts as a per-submission record with a placeholder ready for AI summary insertion. Update Google Document Inserts both summaries directly into the newly created Google Doc: Comprehensive Summary: [Full detailed summary] Abstract Summary: [Conceptual summary] Each doc becomes a polished, shareable insight artifact. Concepts Used in the Workflow Comprehensive Summarization Comprehensive summarization captures every important detail in a factual, exhaustive way — ideal when accuracy and completeness matter. Goal: Provide a detailed understanding of user responses without losing nuance. Best For: Research surveys Customer service logs Support ticket summaries Feedback traceability Abstract Summarization Abstract summarization rephrases and synthesizes ideas, offering high-level insights rather than copying text. Goal: Capture the essence and implications of feedback — ideal for storytelling and executive reviews. Best For: Executive summaries Marketing insights Customer trend analysis Blog-style recaps Setup Instructions Pre-requisite If you are new to Jotform, Please do signup using Jotform Signup For the purpose of demonstation, we are considering the Jotforms Prebuilt Form as a example. Follow these steps to deploy and customize the workflow: Step 0: Local n8n This step is required for the locally hosted n8n only. Please make sure to setup and install ngrok and follow the steps to configure and run ngrok on your local with the n8n port. This is how you can run. ngrok http 5678 Copy the base URL ex: https://2c6ab9f2c746.ngrok-free.app/ as it will be utilized as part of the webhook configuration for the Jotform. Step 1: Configure Jotform Webhook Copy the webhook URL generated by n8n’s Jotform Trigger node. In your Jotform dashboard, go to: Settings → Integrations → Webhooks → Add Webhook If you are executing this workflow on a self hosted n8n instance, please follow the steps for setting up ngrok and format the Webhook URL so that the Jotform can make a Webhook POST over the public URL. Copy the Webhook URL generated by n8n. You can copy the URL by double clicking on the Jotform Trigger node. Make sure to replace the base url with the above Step 0, if you are running the workflow from your local machine. Step 2: Connect Google Gemini Navigate to n8n → Credentials → Google Gemini (PaLM API). Add API credentials and select the model: models/gemini-2.0-flash-exp Test the connection before proceeding. Step 3: Configure the Structured Output Parser Open the Structured Output Parser node. Ensure the schema includes: { "comprehensive_summary": "", "abstract_summary": "" } Modify or expand schema fields if additional summaries (e.g., “sentiment_summary”) are needed. Step 4: Connect Google Sheets Link your Google Sheets OAuth2 credentials. Specify: Document ID (Google Sheet URL) Sheet Name (e.g., “Sheet1”) Map columns to: comprehensive_summary abstract_summary Step 5: Enable DataTable Storage (Optional) Use the DataTable node to maintain a permanent database within n8n Cloud. Configure the schema fields for: comprehensive_summary abstract_summary Step 6: Generate and Update Google Docs Link your Google Docs account under n8n credentials. The workflow auto-creates and updates a doc per submission, embedding both summaries for easy sharing. How to Customize Add Sentiment Analysis** After generating the summary, insert another Google Gemini node to classify the tone of each response — for example, Positive, Neutral, or Negative. This helps you track user sentiment trends over time. Send Alerts for Urgent Feedback** Use an IF node to check if the abstract summary contains words such as “urgent,” “issue,” or “negative.” If triggered, automatically send an alert through Slack, Gmail, or Discord, so the team can respond immediately. Enable Multi-Language Support** Insert a Language Detection node before the Gemini summarizer. Once the language is detected, modify the summarizer prompt dynamically to summarize in that same language — ensuring localized insights. Add Topic Extraction** Include an additional Gemini text extraction node that identifies major topics or recurring themes from each response before summarization. This creates structured insights ready for analytics or tagging. Integrate with CRM or Ticketing Systems** Connect your workflow to HubSpot, Salesforce, or Zendesk to automatically create new records or tickets based on the feedback type or sentiment. This closes the loop between survey collection and actionable response. Summary This workflow automates survey intelligence generation from Jotform submissions — powered by Google Gemini AI — delivering dual-layer summarization outputs directly into Google Sheets, DataTables, and Google Docs. Benefits: Instant comprehensive and abstract summaries per submission. Ready-to-use outputs for reports, dashboards, and client deliverables.