Workflow Templates

Multi-Source RAG System with GPT-4 Turbo, News & Academic Papers Integration This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo. How it works This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo. Key Steps Form Input - Collects user queries with customizable search scope, response style, and language preferences Intelligent Search - Routes queries to appropriate sources (web, academic papers, news, internal documents) Data Aggregation - Unifies and processes information from multiple sources with quality scoring AI Processing - Uses GPT-4 Turbo to generate context-aware, source-grounded responses Response Enhancement - Formats outputs in various styles (comprehensive, concise, technical, etc.) Multi-Channel Delivery - Delivers results via webhook, email, Slack, and optional PDF generation Data Sources & AI Models Search Sources Web Search**: Google, Bing, DuckDuckGo integration Academic Papers**: arXiv, PubMed, Google Scholar News Articles**: News API, RSS feeds, real-time news Technical Documentation**: GitHub, Stack Overflow, documentation sites Internal Knowledge**: Google Drive, Confluence, Notion integration AI Models GPT-4 Turbo**: Primary language model for response generation Embedding Models**: For semantic search and similarity matching Custom Prompts**: Specialized prompts for different response styles Set up steps Setup time: 15-20 minutes Configure API credentials - Set up OpenAI API, ScrapeGraphAI, Google Drive, and other service credentials Set up search sources - Configure academic databases, news APIs, and internal knowledge sources Connect analytics - Link Google Sheets for usage tracking and performance monitoring Configure notifications - Set up Slack channels and email templates for automated alerts Test the workflow - Run sample queries to verify all components are working correctly Keep detailed configuration notes in sticky notes inside your workflow

Run an AI-powered degree audit for each senior student. This template reads student rows from Google Sheets, evaluates completed courses against hard-coded program requirements, and writes back an AI Degree Summary of what's still missing (major core, Gen Eds, major electives, and upper-division credits). It's designed for quick advisor/registrar review and SIS prototypes. Trigger: Manual — When clicking "Execute workflow" Core nodes: Google Sheets, OpenAI Chat Model, (optional) Structured Output Parser Programs included: Computer Science BS, Business Administration BBA, Psychology BA, Mechanical Engineering BS, Biology BS (Pre-Med), English Literature BA, Data Science BS, Nursing BSN, Economics BA, Graphic Design BFA Who's it for Registrars & advisors** who need fast, consistent degree checks Student success teams** building prototype dashboards SIS/EdTech builders** exploring AI-assisted auditing How it works Read seniors from Google Sheets (Senior_data) with: StudentID, Name, Program, Year, CompletedCourses. AI Agent compares CompletedCourses to built-in requirements (per program) and computes Missing items + a short Summary. Write back to the same sheet using "Append or update" by StudentID (updates AI Degree Summary; you can also map the raw Missing array to a column if desired). Example JSON (for one student): { "StudentID": "S001", "Program": "Computer Science BS", "Missing": [ "GEN-REMAIN | General Education credits remaining | 6", "CS-EL-REM | CS Major Electives (200+ level) | 6", "UPPER-DIV | Additional Upper-Division (200+ level) credits needed | 18", "FREE-EL | Free Electives to reach 120 total credits | 54" ], "Summary": "All core CS courses are complete. Still need 6 Gen Ed credits, 6 CS electives, and 66 total credits overall, including 18 upper-division credits — prioritize 200/300-level CS electives." } Setup (2 steps) 1) Connect Google Sheets (OAuth2) In n8n → Credentials → New → Google Sheets (OAuth2) and sign in. In the Google Sheets nodes, select your spreadsheet and the Senior_data tab. Ensure your input sheet has at least: StudentID, Name, Program, Year, CompletedCourses. 2) Connect OpenAI (API Key) In n8n → Credentials → New → OpenAI API, paste your key. In the OpenAI Chat Model node, select that credential and a model (e.g., gpt-4o or gpt-5). Requirements Sheet columns:** StudentID, Name, Program, Year, CompletedCourses CompletedCourses format:** pipe-separated IDs (e.g., GEN-101|GEN-103|CS-101). Program labels:** should match the built-in list (e.g., Computer Science BS). Credits/levels:** Template assumes upper-division ≥ 200-level (adjust the prompt if your policy differs). Customization Change requirements:** Edit the Agent's system message to update totals, core lists, elective credit rules, or level thresholds. Store more output:** Map Missing to a new column (e.g., AI Missing List) or write rows to a separate sheet for dashboards. Distribute results:** Email summaries to advisors/students (Gmail/Outlook), or generate PDFs for advising folders. Add guardrails:** Extend the prompt to enforce residency, capstone, minor/cognate constraints, or per-college Gen Ed variations. Best practices (per n8n guidelines) Sticky notes are mandatory:** Include a yellow sticky note that contains this description and quick setup steps; add neutral sticky notes for per-step tips. Rename nodes clearly:** e.g., "Get Seniors," "Degree Audit Agent," "Update Summary." No hardcoded secrets:** Use credentials—not inline keys in HTTP or Code nodes. Sanitize identifiers:** Don't ship personal spreadsheet IDs or private links in the published version. Use a Set node for config:** Centralize user-tunable values (e.g., column names, tab names). Troubleshooting OpenAI 401/429:** Verify API key/billing; slow concurrency if rate-limited. Empty summaries:** Check column names and that CompletedCourses uses |. Program mismatch:** Align Program labels to those in the prompt (exact naming recommended). Sheets auth errors:** Reconnect Google Sheets OAuth2 and re-select spreadsheet/tab. Limitations Not an official audit:** It infers gaps from the listed completions; registrar rules can be more nuanced. Catalog drift:** Requirements are hard-coded in the prompt—update them each term/year. Upper-division heuristic:** Adjust the level threshold if your institution defines it differently. Tags & category Category: Education / Student Information Systems Tags: degree-audit, registrar, google-sheets, openai, electives, upper-division, graduation-readiness Changelog v1.0.0 — Initial release: Senior_data in/out, 10 programs, AI Degree Summary output, append/update by StudentID. Contact Need help tailoring this to your catalog (e.g., per-college Gen Eds, capstones, minors, PDFs/email)? 📧 rbreen@ynteractive.com 📧 robert@ynteractive.com 🔗 Robert Breen — https://www.linkedin.com/in/robert-breen-29429625/ 🌐 ynteractive.com — https://ynteractive.com

Promo Seeker finds fresh, working promo codes and vouchers on the web so your team never misses a deal. This n8n workflow uses SerpAPI and Decodo Scrapper for real-time search, an agent powered by GPT-5 Mini for filtering and validation, and Chat Memory to keep context—saving time, reducing manual checks, and helping marketing or customer support teams deliver discounts faster to customers (and yes, it's better at hunting promos than your inbox). 💡 Why Use Promo Seeker? Speed: Saves hours per week by automatically finding and validating current promo codes, so you can publish deals faster. Simplicity: Eliminates manual searching across sites, no more copy-paste scavenger hunts. Accuracy: Reduces false positives by cross-checking results and keeping only working vouchers—fewer embarrassed "expired code" moments. Edge: Combine search APIs with an AI agent to surface hard-to-find, recently-live offers—win over competitors who still rely on manual scraping. ⚡ Perfect For Marketing teams: Quickly populate newsletters, landing pages, or ads with valid promos. Customer support: Give verified discount codes to users without ping-ponging between tabs. Deal aggregators & affiliates: Discover fresh vouchers faster and boost conversion rates. 🔧 How It Works ⏱ Trigger: A user message via the chat webhook starts the search (Message node). 📎 Process: The agent queries SerpAPI and Decodo Scrapper to collect potential promo codes and voucher pages. 🤖 Smart Logic: The Promo Seeker Agent uses GPT-5 Mini with Chat Memory to filter for fresh, working promos and to verify validity and relevance. 💌 Output: Results are returned to the chat with clear, copy-ready promo codes and source links. 🗂 Storage: Chat Memory stores context and recent searches so the agent avoids repeating old results and can follow up with improved queries. 🔐 Quick Setup Import JSON file to your n8n instances Add credentials: SerpAPI, Azure OpenAI (Gpt 5 Mini), Decodo API Customize: Search parameters (brands, regions, validity window), agent system message, and result formatting Update: Azure OpenAI endpoint and API key in the Gpt 5 Mini credentials; add your SerpAPI key and Decodo key Test: Run a few queries like "latest Amazon promo" or "food delivery voucher" and confirm returned codes are valid 🧩 You'll Need Active n8n instances SerpAPI account and API key Azure OpenAI (for GPT-5 Mini) with key and endpoint Decodo account/API key 🛠️ Level Up Ideas Push verified promos to a Slack channel or email digest for the team. Add scheduled scans to detect newly expired codes and remove them from lists. Integrate with a CMS to auto-post verified deals to landing pages. Made by: khaisa Studio Tags: promo, vouchers, discounts Category: Marketing Automation Need custom work? Contact Us

[Workflow Overview] ⚠️ Self-Hosted Only: This workflow uses the gotoHuman community node and requires a self-hosted n8n instance. Who's It For Content teams, bloggers, news websites, and marketing agencies who want to automate content creation from RSS feeds while maintaining editorial quality control. Perfect for anyone who needs to transform news articles into detailed blog posts at scale. What It Does This workflow automatically converts RSS feed articles into comprehensive, SEO-optimized blog posts using AI. It fetches articles from your RSS source, generates detailed content with GPT-4, sends drafts for human review via gotoHuman, and publishes approved articles to Google Docs with automatic Slack notifications to your team. How It Works Schedule Trigger runs every 6 hours to check for new RSS articles RSS Read node fetches the latest articles from your feed Format RSS Data extracts key information (title, keywords, description) Generate Article with AI creates a structured blog post using OpenAI GPT-4 Structure Article Data formats the content with metadata Request Human Review sends the article for approval via gotoHuman Check Approval Status routes the workflow based on review decision Create Google Doc and Add Article Content publish approved articles Send Slack Notification alerts your team with article details Requirements OpenAI API key** with GPT-4 access Google account** for Google Docs integration gotoHuman account** for human-in-the-loop approval workflow Slack workspace** for team notifications RSS feed URL** from your preferred source How to Set Up Configure RSS Feed: In the "RSS Read" node, replace the example URL with your RSS feed source Connect OpenAI: Add your OpenAI API credentials to the "OpenAI Chat Model" node Set Up Google Docs: Connect your Google account and optionally specify a folder ID for organized storage Configure gotoHuman: Add your gotoHuman credentials and create a review template for article approval Connect Slack: Authenticate with Slack and select the channel for notifications Customize Content: Modify the AI prompt in "Generate Article with AI" to match your brand voice and article structure Adjust Schedule: Change the trigger frequency in "Schedule Trigger" based on your content needs How to Customize Article Style**: Edit the AI prompt to change tone, length, or structure Keywords & SEO**: Modify the "Format RSS Data" node to adjust keyword extraction logic Publishing Destination**: Change from Google Docs to other platforms (WordPress, Notion, etc.) Approval Workflow**: Customize the gotoHuman template to include specific review criteria Notification Format**: Adjust the Slack message template to include additional metadata Processing Volume**: Modify the Code node to process multiple RSS articles instead of just one

Video Introduction Want to automate your inbox or need a custom workflow? 📞 Book a Call | 💬 DM me on Linkedin Workflow Overview This workflow creates an intelligent AI chatbot that retrieves recipes from an external API through natural conversation. When users ask for recipes, the AI agent automatically determines when to use the recipe lookup tool, fetches real-time data from the API Ninjas Recipe API, and provides helpful, conversational responses. This demonstrates the powerful capability of API-to-API integration within n8n, allowing AI agents to access external data sources on demand. Key Features Intelligent Tool Calling:** The AI agent automatically decides when to use the HTTP Request Tool based on user queries External API Integration:** Connects to API Ninjas Recipe API using Header Authentication for secure access Conversational Memory:** Maintains context across multiple turns for natural dialogue Dynamic Query Generation:** The AI model automatically generates the appropriate search query parameters based on user input Common Use Cases Build AI assistants that need access to real-time external data Create chatbots with specialized knowledge from third-party APIs Demonstrate API-to-API integration patterns for custom automation Prototype AI agents with tool-calling capabilities Setup & Configuration Required Credentials: OpenAI API: Sign up at OpenAI and obtain an API key for the language model. Configure this in n8n's credential manager. API Ninjas: Register at API Ninjas to get your free API key for the Recipe API (supports 400+ calls/day). This API uses Header Authentication with the header name "X-Api-Key". Agent Configuration: The AI Agent includes a system message instructing it to "Always use the recipe tool if i ask you for recipe." This ensures the agent leverages the external API when appropriate. The HTTP Request Tool is configured with the API endpoint (https://api.api-ninjas.com/v1/recipe) and set to accept query parameters automatically from the AI model. The tool description "Use the query parameter to specify the food, and it will return a recipe" helps the AI understand when and how to use it. Language Model: Currently configured to use OpenAI's gpt-5-mini, but you can change this to other compatible models based on your needs and budget. Memory: Uses a window buffer to maintain conversation context, enabling natural multi-turn conversations where users can ask follow-up questions.

Description Save hours of manual reporting with this end-to-end automation. This workflow pulls campaign performance data (demo or live), generates a clear AI-powered executive summary, and compiles everything into a polished weekly report. The report is formatted in Markdown, automatically stored in Google Docs, and instantly shared with your team via Slack — no spreadsheets, no copy-paste, no delays. What it does ⏰ Runs on a schedule (e.g. every Monday morning) 📊 Collects performance metrics (Google Ads, Meta, TikTok, YouTube – demo data included) 🤖 Uses AI to summarize wins, issues, and recommendations 📝 Builds a structured Markdown report (totals, channel performance, top campaigns) 📄 Creates and updates a Google Doc with the report 💬 Notifies your team in Slack with topline numbers + direct report link 📧 Optionally email the report to stakeholders or clients Why it’s valuable Saves time** – no manual data aggregation Standardizes reporting** – same format and quality every week Adds insights** – AI highlights what matters most Improves transparency** – instant access via Docs, Slack, or Email Scales easily** – adapt to multiple clients or campaigns Professional delivery** – branded, polished reports on autopilot 💡 Extra recommendation: Connect to a Google Docs template to give your reports a professional, branded look.

Automated daily swing‑trade ideas from end‑of‑day (EOD) data, scored by an LLM, logged to Google Sheets, and pushed to Telegram. What this workflow does Fetches EOD quotes* for a chosen stock universe (example: *NSE‑100** via RapidAPI). Cleans & filters** the universe using simple technical/quality gates (e.g., price/volume sanity, avoid illiquid names). Packages market context* and feeds it to *OpenAI* with a strict *JSON schema* to produce *top swing‑trade recommendations** (entry, target, stop, rationale). Splits structured output* into rows and *logs* them to a *Google Sheet** for tracking. Sends an alert* with the day’s trade ideas to *Telegram** (channel or DM). Ideal for Retail traders who want a daily, hands‑off idea generator. PMs/engineers prototyping LLM‑assisted quant sidekicks. Creators who publish daily trade notes to their audience. Tech stack n8n** (orchestration) RapidAPI** (EOD quotes; pluggable data source) OpenAI** (LLM for idea generation) Google Sheets** (logging & performance tracker) Telegram** (alerts) Prerequisites RapidAPI key with access to an EOD quotes endpoint for your exchange. OpenAI API key. Google account with a Sheet named Trade_Recommendations_Tracker (or update the node). Telegram bot token (via @BotFather) and destination chat ID. > You can replace any of the above vendors with equivalents (e.g., Alpha Vantage, Twelve Data, Polygon, etc.). Only the HTTP Request + Format nodes need tweaks. Environment variables | Key | Example | Used in | | -------------------- | -------------------------- | --------------------- | | RAPIDAPI_KEY | xxxxxxxxxxxxxxxxxxxxxxxx | HTTP Request (quotes) | | OPENAI_API_KEY | sk-… | OpenAI node | | TELEGRAM_BOT_TOKEN | 123456:ABC-DEF… | Telegram node | | TELEGRAM_CHAT_ID | 5357385827 | Telegram node | Google Sheet schema Create a Sheet (tab: EOD_Ideas) with the headers: Date, Symbol, Direction, Entry, Target, StopLoss, Confidence, Reason, SourceModel, UniverseTag Node map (name → purpose) Trigger – Daily Market Close → Fires daily after market close (e.g., 4:15 PM IST). Prepare Stock List (NSE 100) → Provides stock symbols to analyze (static list or from a Sheet/API). Fetch EOD Data (RapidAPI) → Gets EOD data for all symbols in one or batched calls. Format EOD Data → Normalizes API response to a clean array (symbol, close, high, low, volume, etc.). Filter Valid Stock Data → Drops illiquid/invalid rows (e.g., volume > 200k, close > 50). Build LLM Prompt Input → Creates compact market context & JSON instructions for the model. Generate Swing Trade Ideas (OpenAI) → Returns strict JSON with top ideas. Split JSON Output (Trade‑wise) → Explodes the JSON array into individual items. Log Trade to Google Sheet → Appends each idea as a row. Send Trade Alert to Telegram → Publishes a concise summary to Telegram.

Blockify® Technical Manual Data Optimization Workflow Blockify Optimizes Data for Technical Manual RAG and Agents - Giving Structure to Unstructured Data for ~78X Accuracy, when pairing Blockify Ingest and Blockify Distill Learn more at https://iternal.ai/blockify Get Free Demo API Access here: https://console.blockify.ai/signup Read the Technical Whitepaper here: https://iternal.ai/blockify-results See example Accuracy Comparison here: https://iternal.ai/case-studies/medical-accuracy/ Blockify is a data optimization tool that takes messy, unstructured text, like hundreds of sales‑meeting transcripts or long proposals, and intelligently optimizes the data into small, easy‑to‑understand "IdeaBlocks." Each IdeaBlock is just a couple of sentences in length that capture one clear idea, plus a built‑in contextualized question and answer. With this approach, Blockify improves accuracy of LLMs (Large Language Models) by an average aggregate 78X, while shrinking the original mountain of text to about 2.5% of its size while keeping (and even improving) the important information. When Blockify's IdeaBlocks are compared with the usual method of breaking text into equal‑sized chunks, the results are dramatic. Answers pulled from the distilled IdeaBlocks are roughly 40X more accurate, and user searches return the right information about 52% more accurate. In short, Blockify lets you store less data, spend less on computing, and still get better answers- turning huge documents into a concise, high‑quality knowledge base that anyone can search quickly. Blockify works by processing chunks of text to create structured data from an unstructured data source. Blockify® replaces the traditional "dump‑and‑chunk" approach with an end‑to‑end pipeline that cleans and organizes content before it ever hits a vector store. Admins first define who should see what, then the system ingests any file type—Word, PDF, slides, images—inside public cloud, private cloud, or on‑prem. A ​context‑aware splitter finds natural breaks, and a series of specially developed Blockify LLM model turns each segment into a draft IdeaBlock. GenAI systems fed with this curated data return sharper answers, hallucinate far less, and comply with security policies out of the box. The result: higher trust, lower operating cost, and a clear path to enterprise‑scale RAG without the cleanup headaches that stall most AI rollouts.

Who's it for This template is perfect for any SaaS business or subscription service using Stripe. Product managers, customer success teams, and founders can use this to automatically collect cancellation feedback without manual follow-up. Ideal for companies looking to reduce churn by understanding why customers leave. What it does When a customer cancels their Stripe subscription, this workflow instantly: Detects the cancellation via Stripe webhook Fetches customer details from Stripe API Sends a personalized feedback survey email with embedded customer information Logs all cancellations to Google Sheets for tracking Receives survey responses via webhook Automatically routes feedback to different Google Sheets based on reason (pricing concerns, feature requests, or other feedback) This organized approach helps you identify patterns in cancellations and prioritize improvements that matter most. How it works Stripe triggers the workflow when a subscription is canceled Customer data is fetched from the Stripe API (email, name, plan details) Personalized email is sent with a survey link containing customer data as URL parameters Cancellation is logged to a Google Sheets "Cancellations" tab When the customer submits the survey, a webhook receives the response Feedback is routed to dedicated sheets based on cancellation reason: Price Concerns → for pricing-related issues Feature Requests → for missing functionality Other Feedback → for everything else Set up steps Setup time: ~20 minutes Prerequisites Stripe account (test mode recommended for initial setup) Google account with Google Sheets Email service (Gmail, Outlook, or SMTP) Survey tool with webhook support (Tally or Typeform recommended) Configuration Stripe webhook: Copy the webhook URL from the "Stripe Subscription Canceled" node and add it to your Stripe Dashboard → Webhooks. Select the customer.subscription.deleted event. Email credentials: Configure Gmail, Outlook, or SMTP credentials in the "Send Feedback Survey Email" node. Update the fromEmail parameter. Survey form: Create a survey form with these fields: Hidden fields (auto-populated from URL): email, customer_id, name, plan Visible fields: reason dropdown ("Too Expensive", "Missing Features", "Other"), comments textarea Configure webhook to POST responses to the "Survey Response Webhook" URL Google Sheets: Create a spreadsheet with 4 sheets: "Cancellations", "Price Concerns", "Feature Requests", and "Other Feedback". Connect your Google account in the Google Sheets nodes. Survey URL: Replace [SURVEY_URL] in the email template with your actual survey form URL. Test: Use Stripe test mode to trigger a test cancellation and verify the workflow executes correctly. Requirements Stripe account with API access Google Sheets (free) Email service: Gmail, Outlook, or SMTP server Survey tool: Tally (free), Typeform (paid), or custom form with webhook capability n8n instance: Cloud or self-hosted How to customize Different surveys by plan: Add an IF node after getting customer details to send different survey links based on subscription tier Slack notifications: Add a Slack node after "Route by Feedback Type" to alert your team about price concerns in real-time Delayed email: Insert a Wait node before sending the email to give customers a 24-hour cooldown period CRM integration: Add nodes to sync cancellation data with your CRM (HubSpot, Salesforce, etc.) Follow-up workflow: Create a separate workflow that triggers when feedback is received to send personalized follow-up offers Custom routing logic: Modify the Switch node conditions to match your specific survey options or add more categories Tips for success Use Stripe test mode initially to avoid sending emails to real customers during setup Customize the email tone to match your brand voice Keep the survey short (2-3 questions max) for higher response rates Review feedback weekly to identify patterns and prioritize improvements Consider offering a discount or incentive for completing the survey

Build a Customer Support AI Voice Agent with GPT-5 and ElevenLabs 👥 Who is this for? This template is ideal for: Businesses that want to provide 24/7 automated voice-based customer support Service providers needing to schedule appointments via voice interaction Teams looking to handle multilingual customer queries automatically Entrepreneurs aiming to boost customer engagement without hiring large support teams 💡 What problem is this workflow solving? Traditional customer support requires: Human agents to answer repeated questions Manual handling of bookings and confirmations Limited availability outside office hours This workflow solves those issues by combining GPT-5 intelligence with ElevenLabs voice synthesis, enabling your website visitors to: Ask questions and receive spoken answers in multiple languages Request appointment availability Confirm bookings and receive automatic email confirmations All of this happens automatically, reducing costs and ensuring consistent customer experience. ⚙️ What this workflow does Receive customer voice input via webhook from your website Transcribe and understand intent using GPT-5 and LangChain reasoning Fetch information from your knowledge base (Google Sheets) for FAQs, services, or policies Check availability in Google Calendar in real-time Create confirmed appointments only after explicit user confirmation Send confirmation emails with booking details via Gmail Respond back to the user with a multilingual spoken reply using ElevenLabs 🧰 Setup Before launching this workflow, make sure you: Have an OpenAI API key for GPT-5 Set up an ElevenLabs account and API key for voice input/output Enable Google Sheets API and prepare a sheet with your FAQ/knowledgebase Enable Google Calendar API and connect your calendar for scheduling Connect your Gmail account for booking confirmation emails Configure the Webhook URL on your website for sending voice requests Follow the sticky note instructions inside the workflow for final setup 🛠️ How to customize this workflow Knowledgebase:** Add or update information in your Google Sheets to cover new FAQs Voice settings:** Configure ElevenLabs voice style, tone, or supported languages Appointment rules:** Adjust event duration or add reschedule/cancellation options Notifications:** Add Slack or Telegram alerts for each new confirmed booking Email templates:** Customize the confirmation email with your brand style With this workflow, your website becomes an AI-powered voice assistant — capable of handling customer inquiries, providing multilingual support, and managing bookings seamlessly. 📄 Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube

📝 Description This n8n workflow automates the candidate shortlisting process by integrating Google Sheets, Gmail, ClickUp, and Calendly. It fetches candidate records, filters high-scoring profiles, sends personalized advancement emails, and creates screening tasks for your HR team—all with a single manual trigger. 🚀 What It Does Fetch All Candidate Records Retrieves complete candidate data (names, scores, contact info, summaries) from the ‘Resume store’ Google Sheet (Sheet2). Efficiently loads all rows for batch analysis. Filter High-Score Candidates Applies a threshold filter (default: score > 70) to identify strong-fit candidates. Only qualified profiles advance; threshold is customizable per role. Send Congratulations Email Sends personalized emails to qualified candidates using Gmail. Includes a dynamic Calendly scheduling link for interview booking. Maintains a positive candidate experience with professional messaging. Create Screening Task in ClickUp Automatically generates screening tasks for each qualified candidate in ClickUp. Assigns tasks to a designated team member and organizes them in specified project folders. Ensures accountability and seamless follow-up. 📈 Key Benefits Speed: Instantly advances qualified candidates—no manual sorting. Consistency: Standardized criteria and communications for every role. Organization: Auto-creates ClickUp tasks so nothing slips through. Experience: Timely, professional communication enhances candidate journey. Efficiency: Reduces HR workload and error risk. ⚙️ Customization & Integration Score Threshold: Set to 70 by default; adjust for different roles or seniority. Email Template: Editable subject, body, and CTA (Calendly link). ClickUp Integration: Uses configurable Team, Space, Folder, List, and Assignee IDs. Systems Supported: Google Sheets (data), Gmail (email), ClickUp (tasks), Calendly (scheduling). 🔧 Setup Requirements n8n instance (self-hosted or cloud). Google Sheets access for ‘Resume store’ (Sheet2). Gmail credentials for candidate notifications. ClickUp API token and IDs for task creation. Calendly link for interview scheduling. 👥 Target Audience HR teams, recruiters, staffing agencies. Operations managing high-volume candidate pipelines. Startups/SMBs seeking standardized hiring automation. 🛠️ Maintenance Tips Update email templates seasonally. Review scoring thresholds monthly. Monitor ClickUp task completion rates. Ensure Calendly links remain active. 📋 Step-by-Step Usage Connect Google Sheets, Gmail, and ClickUp credentials in n8n. Import the workflow; configure threshold, email, and ClickUp settings. Edit the email node with your Calendly link and branding. Trigger “Execute workflow” after new candidate scores are added. Review logs and results for successful candidate progression.

This n8n workflow automatically detects canceled meetings from Calendly, uses GPT to write a friendly follow-up message, and sends it via Gmail, complete with a personalized Loom video link. It also creates an Asana task to remind your team to follow up manually if needed. Ideal for B2B consultants, agencies, and sales teams who want to salvage missed opportunities and stay top-of-mind with prospects after no-shows. ⸻ Who it’s for Sales teams, consultants, and agencies who rely on scheduled calls to close business and want to re-engage leads who cancel or no-show using automated, human-sounding follow-ups. ⸻ How it works / What it does A Calendly Webhook triggers the flow when a meeting is canceled. Edit Fields extracts the meeting details (who canceled, when, and why). A GPT-4 node writes a personalized follow-up email based on the meeting context. You manually paste in your Loom video link. A Merge node combines the AI-written message, user info, and video link. Gmail sends the follow-up message automatically to the contact. An Asana task is created for your team to track the missed call and optionally follow up manually. ⸻ How to set up Create a webhook in Calendly and connect it to the Calendly Trigger node. Add your OpenAI key in the Message a Model node. Connect your Gmail and Asana accounts via n8n credentials. Manually paste in the Loom video link in the Loom Link node. Set your preferred Asana project and teammate in the Create a Task node. ⸻ Requirements A Calendly account OpenAI API key Gmail account with OAuth connected in n8n Asana account with access to a project and user ID ⸻ How to customize the workflow Update the GPT prompt to change the tone or add context based on your business. Replace Loom with a Vidyard, Tella, or custom-hosted video link. Add a Slack notification node to alert your sales team when a call is missed. Link with a CRM or Google Sheets to track follow-up activity across your pipeline. This modular workflow helps you turn no-shows into new opportunities, while keeping your team organized and your leads engaged.