Workflow Templates

Personal AI Assistant on Telegram Who It’s For: This workflow is designed for developers, founders, community managers, and automation enthusiasts who want to bring a personal AI assistant directly into their Telegram chat. It lets users interact naturally—either through text or voice messages—and get instant, AI-powered replies without switching apps or opening dashboards. ⚡ What It Does / How It Works 📥 Message Trigger: A Telegram Trigger node listens for incoming messages. 🧭 Smart Routing: A Switch node decides if the user sent a text or voice message. 🗣️ Voice to Text: If it’s voice, the workflow uses OpenAI Whisper Transcription to convert it into text. 🧠 AI Processing: The text is passed to an AI Agent powered by GPT-4.1-mini to understand intent and craft a response. 💬 Reply: The bot sends a clean, structured, and polite answer back to the user on Telegram. 🧠 Memory: A buffer memory node keeps short-term conversation history for a more contextual, human-like experience. 🧰 How to Set It Up: Telegram Integration Create a bot via @BotFather on Telegram. https://telegram.me/BotFather Add your Telegram API Key to n8n credentials. Connect the Telegram Trigger and Send a Message nodes. OpenAI Setup Get your API key from platform.openai.com. https://platform.openai.com/api-keys Configure the OpenAI Chat Model and Transcribe a Recording nodes with GPT-4.1-mini. Workflow Logic Use the Switch node to detect message type (text or voice). Route voice messages through transcription before sending them to the AI agent. Add Simple Memory to maintain short conversational context. Go Live Activate the workflow. Send a message or voice note to your bot. Get instant replies from your personal AI assistant. 🚀 🛡️ Requirements: n8n (self-hosted or cloud) Telegram Bot API key OpenAI API key (for GPT-4.1-mini) Basic understanding of n8n nodes and connections 🌟 Why Use This Workflow: ✅ Hands-free experience: Just talk or type. 🧠 AI-powered responses: Natural language understanding with GPT. ⚡ Real-time interaction: Fast replies via Telegram. 🔁 Memory-aware conversations: Feels more human. 🧩 Modular design: Easily extend to other AI tools or platforms.

Create a Fall 2025 course schedule for each student based on what they’ve already completed, catalog prerequisites, and term availability (Fall/Both). Reads students from Google Sheets → asks an AI agent to select exactly 5 courses (target 15–17 credits, no duplicates, prereqs enforced) → appends each student’s schedule to a schedule tab. 🧠 Summary Trigger:* Manual — *“When clicking ‘Execute workflow’” I/O:** Google Sheets in → OpenAI decisioning → Google Sheets out Ideal for:** Registrars, advisors, degree-planning prototypes ✅ What this template does Reads: StudentID, Name, Program, Year, CompletedCourses (pipe-separated CourseIDs) from **Sheet1 Decides: AI **Scheduling Agent chooses 5 courses per student following catalog rules and prerequisites Writes: Appends StudentID + Schedule strings to **schedule worksheet Credits target**: 15–17 total per term Catalog rules** (enforced in the agent prompt): Use Fall or Both courses for Fall 2025 Enforce AND prereqs (e.g., CS-102|CS-103 means both) Priority: Major Core → Major Elective → Gen Ed (include Gen Ed if needed) No duplicates or already-completed courses Prefer 200-level progression when prereqs allow ⚙️ Setup (only 2 steps) 1) Connect Google Sheets (OAuth2) In n8n → Credentials → New → Google Sheets (OAuth2), sign in and grant access In the Google Sheets nodes, select your spreadsheet and these tabs: Sheet1 (input students) schedule (output) > Example spreadsheet (replace with your own): > - Input: .../edit#gid=0 > - Output: .../edit#gid=572766543 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 chat model (e.g., gpt-4o) 📥 Required input (Sheet1) Columns**: StudentID, Name, Program, Year, CompletedCourses CompletedCourses**: pipe-separated IDs (e.g., GEN-101|GEN-103|CS-101) Program* names should match those referenced in the embedded catalog (e.g., *Computer Science BS, Business Administration BBA, etc.) 📤 Output (schedule tab) Columns**: StudentID Schedule → a selected course string (written one row per course after splitting) 🧩 Nodes in this template Manual Trigger* → *Get Student Data (Google Sheets)* → *Scheduling Agent (OpenAI)** → Split Schedule → Set Fields → Clear sheet → Append Schedule (Google Sheets) 🛠 Configuration tips If you rename tabs, update both Get Student Data and Append Schedule nodes Keep CompletedCourses consistent (use | as the delimiter) To store rationale as well, add a column to the output and map it from the agent’s JSON 🧪 Test quickly 1) Add 2–3 sample student rows with realistic CompletedCourses 2) Run the workflow and verify: 5 course rows per student in schedule Course IDs respect prereqs & Fall/Both availability Credits sum ~15–17 🧯 Troubleshooting Sheets OAuth error:** Reconnect “Google Sheets (OAuth2)” and re-select the spreadsheet & tabs Empty schedules:** Ensure CompletedCourses uses | and that programs/courses align with the provided catalog names Prereq violations:** Check that students actually have all AND-prereqs in CompletedCourses OpenAI errors (401/429):** Verify API key, billing, and rate-limit → retry with lower concurrency 🔒 Privacy & data handling Student rows are sent to OpenAI for decisioning. Remove or mask any fields you don’t want shared. Google Sheets retains input/output. Use spreadsheet sharing controls to limit access. 💸 Cost & performance OpenAI**: Billed per token; cost scales with student count and prompt size Google Sheets**: Free within normal usage limits Runtime**: Typically seconds to a minute depending on rows and rate limits 🧱 Limitations & assumptions Works for Fall 2025 only (as written). For Spring, update availability rules in the agent prompt Assumes catalog in the agent system message is your source of truth Assumes Program names match catalog variants (case/spacing matter for clarity) 🧩 Customization ideas Add a Max Credits column to cap term credits per student Include Rationale in the sheet for advisor review Add a “Gen Ed needed?” flag per student to force at least one Gen Ed selection Export to PDF or email the schedules to advisors/students 🧾 Version & maintenance n8n version:** Tested on recent n8n Cloud builds (2025) Community nodes:** Not required Maintenance:** Update the embedded catalog and offerings each term; keep prerequisites accurate 🗂 Tags & category Category:** Education / Student Information Systems Tags:** scheduling, registrar, google-sheets, openai, prerequisites, degree-planning, catalog, fall-term 🗒 Changelog v1.0.0** — Initial release: Sheets in/out, Fall 2025 catalog rules, prereq enforcement, 5-course selection, credits target 📬 Contact Need help customizing this (e.g., cohort logic, program-specific rules, adding rationale to the sheet, or emailing PDFs)? 📧 rbreen@ynteractive.com 🔗 Robert Breen — https://www.linkedin.com/in/robert-breen-29429625/ 🌐 ynteractive.com — https://ynteractive.com

Replace BillyBot: Free Slack Employee Birthday & Anniversary Automation Who's it for HR teams, team leaders, and operations managers looking to automate employee celebrations without expensive third-party tools like BillyBot. Perfect for startups to enterprise teams wanting to save $600-2,400+ annually while maintaining personalized, engaging employee recognition. What it does This workflow automatically monitors your employee database daily and posts AI-generated, unique celebration messages to Slack for birthdays and work anniversaries. Unlike generic bots, it creates personalized messages that never repeat, rotating through 12 different styles and tones to keep celebrations fresh and authentic. How it works Daily Check: Runs every morning at 9 AM to scan your employee Google Sheet Smart Filtering: Matches today's date against employee birthdays and joining dates Data Aggregation: Collects all celebrating employees into a single payload AI Generation: Google Gemini creates unique, heartfelt messages with proper Slack formatting Auto-Post: Sends personalized celebrations directly to your chosen Slack channel The AI ensures no two messages feel templated, calculating years of service for anniversaries and adapting tone based on tenure length. Requirements Google Sheets** with employee data (columns: NO, Name, Email, Date of Birth, Joining Date in YYYY-MM-DD format) Slack workspace** with bot permissions to post messages Google Gemini API key** (free tier included) n8n Cloud** ($20/month) or self-hosted n8n (free) Cost comparison: Save $600-2,400+ per year BillyBot pricing: $1 per employee/month 50 employees = $600/year 100 employees = $1,200/year 200 employees = $2,400/year This solution: $0-20/month (unlimited employees) Google Gemini API: FREE Google Sheets API: FREE Slack API: FREE n8n: $20/month (Cloud) or $0 (self-hosted) Your savings: 95-100% cost reduction regardless of team size. Setup instructions Create Google Sheet: Add columns: NO, Name, Email, Date of Birth, Joining Date (ensure dates are YYYY-MM-DD format) Connect Google Sheets: Authenticate your Google account in the "Get row(s) in sheet" node Set up Slack: Create a Slack bot with chat:write permission and add to your celebration channel Configure Gemini: Add your Google Gemini API key to the "Google Gemini Chat Model" node Adjust Schedule: Change trigger time in "Schedule Trigger" node (default: 9 AM daily) Select Channel: Update Slack channel in "Send a message" node to your desired celebration channel Test: Run workflow manually to verify messages post correctly Customization options Change celebration time**: Modify the Schedule Trigger to any hour (e.g., 8 AM for morning celebrations) Adjust message tone**: Edit the AI Agent system prompt to match your company culture (formal, casual, playful) Multi-channel posting**: Duplicate the Slack node to post to multiple channels (e.g., company-wide + team-specific) Add upcoming reminders**: Modify the IF node to check for celebrations within 7 days Include photos**: Extend the workflow to pull employee photos from your HR system Custom emoji styles**: Update the AI prompt to use your organization's custom Slack emojis Key features 12 rotating message styles prevent repetition Automatic tenure calculation for work anniversaries Culturally inclusive and professional tone Mobile-optimized message length (1-3 lines) Slack markdown formatting for visual appeal Scales infinitely without additional cost Note: Ensure your Google Sheet date formats are consistent (YYYY-MM-DD) for accurate date matching. The workflow processes dates in MM-DD format to match across years automatically.

Workflow Description: Turn a simple text idea into production-ready icons in seconds. With this workflow, you input a subject (e.g., “Copy”, “Banana”, “Slack Mute”), select a style (Flat, 3D, Cartoon, etc.), and off it goes. Here’s what happens: A form trigger collects your icon subject, style and optional background. The workflow uses an LLM to construct an optimised prompt. An image-generation model (OpenAI image API) renders a transparent-background, 400×400 px PNG icon. The icon is automatically uploaded to Google Drive, and both a download link and thumbnail are generated. A styled completion card displays the result and gives you a “One More Time” option. Perfect for designers, developers, no-code creators, UI builders and even home-automation geeks (yes, you can integrate it with Home Assistant or Stream Deck!). It saves you the manual icon-hunt grind and gives consistent visual output across style variants. 🔧 Setup Requirements: n8n instance (self-hosted or cloud) OpenAI API access (image generation enabled) Google Drive credentials (write access to a folder) (Optional) Modify to integrate Slack, Teams or other file-storage destinations ✅ Highlights & Benefits: Fully automated prompt creation → consistent icon quality Transparent background PNGs size-ready for UI use Saves icons to Drive + gives immediate link/thumbnail Minimal setup, high value for creative/automation workflows Easily extendable (add extra sizes, style presets, share via chat/bot) ⚠️ Notes & Best-Practices: Check your OpenAI image quota and costs - image generation may incur usage. Confirm Google Drive folder permissions to avoid upload failures. If you wish a different resolution or format (e.g., SVG), clone the image node and adjust parameters.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 🤖 AI-Powered Twitter Content Generator Transform topic ideas into ready to post Twitter drafts (text + image) using fresh web data and AI agents 🎯 What does this workflow do? This end to end automation creates complete Twitter posts by: Taking your topic input (e.g., "Agentic AI") via chat interface Generating fresh, research-backed content using AI agents: First agent uses GPT-4.1-MINI + Tavily to bypass LLM knowledge limits with real-time web data Second agent creates optimized prompt for image generation Producing custom visuals through OpenAI's gpt-image-1 Delivering polished drafts (text + image) via Gmail for review ⚙️ How it works User input: You provide a topic through chat node Content research: Agent 1 (GPT-4.1-mini + Tavily) researches current web data Generates factually fresh tweet content Visual creation: Agent 2 optimizes prompt for image generation HTTP request node calls OpenAI's gpt-image-1 model to generate the image Convert to file node converst the base64 string to a file so we can send it as an attachment Delivery: Gmail node sends compiled draft with text body + image attachment 🔑 Required setup Have a verified organization: OpenAI Org Settings OpenAI API Key: Create a Key Here Tavily API Key: Get it Here Gmail credentials: Google Cloud Console

This workflow fetches live financial data from SerpApi and generates a daily market recap using OpenAI. ⚙️ Setup Instructions 1️⃣ Set Up SerpApi Connection Create a free account at SerpApi Copy your API Key from the SerpApi dashboard In n8n → Credentials → New → SerpApi Paste your API Key → Save In the workflow, select your SerpApi credential in the Finance Search node. 2️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 🧠 How it works SerpApi Finance Search** → pulls market data (example: S&P 500, ticker ^GSPC) OpenAI Model** → summarizes into a daily report with a paragraph + key bullet points 📬 Contact Need help customizing (e.g., pulling multiple tickers, exporting to Google Sheets, or sending Slack/Email updates)? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

Appointment Reminder Agent automates phone call reminders for upcoming appointments by seamlessly connecting Google Calendar with Retell AI. This powerful workflow is designed to help businesses, clinics, and service providers ensure clients never miss their scheduled appointments—reducing no-shows and increasing efficiency. ##Use Cases Healthcare practitioners reminding patients of upcoming visits Salons, spas, and beauty services confirming bookings Consultants, therapists, and coaches sending appointment reminders Any service-based business wanting to reduce missed appointments ##Workflow Overview Trigger – A scheduler node runs every day at 9 AM (configurable) to start the workflow. Fetch Events – Pulls all events scheduled in the next 12 hours from Google Calendar. Extract Details – A Code node parses each event’s description for: Name Phone number (must be in E.164 format, e.g., +14155552671) Reason for appointment Start and end time Configure Retell – Uses credentials to set up: from_number (Retell-registered phone number) agent_id (Retell agent ID) Send Call – Calls Retell AI’s API to place a personalized reminder call to the client. ##Setup Instructions Add your Retell API key to n8n credentials (never hardcode it). Add your Google Calendar account to credentials. Set the from_number (Retell-registered number). Set the agent_id (Retell agent ID). Ensure all calendar event descriptions include required fields (Name, Phone number, Reason, Start & End times) in the specified format. Adjust the scheduler trigger time if needed. ##Requirements Retell AI account with API key Registered Retell phone number Google Calendar account Event descriptions formatted properly with all required details ##Customization Options Modify the trigger schedule (e.g., nightly, hourly, or webhook-based). Add logging or tracking (e.g., use Google Sheets or Airtable to log call attempts/results). Tailor the Retell agent script to suit different appointment types (e.g., “Consultation,” “Follow-up,” “Service Visit”). Expand with additional channels (e.g., SMS or email reminders before or after calls).

How It Works This workflow automates daily contract monitoring, analysis, and negotiation by retrieving contract data, applying AI-driven legal analysis, identifying potential issues and risks, coordinating multi-agent negotiation workflows, and updating strategic plans. It continuously monitors contracts, performs GPT-4–based contract analysis with detailed risk identification, and flags problematic clauses and unfavorable terms. The system routes identified items to a negotiation agent for structured strategic discussion, applies financial impact analysis to evaluate deal implications, determines negotiation outcomes, logs decisions and results, and updates CAPEX and OPEX planning systems accordingly. Designed for legal departments, procurement teams, corporate counsel, and contract management offices, it supports automated contract risk assessment, informed negotiations, and data-driven strategic planning. Setup Steps Configure contract data source and set up daily monitoring schedule. Connect OpenAI GPT-4 API Set up negotiation agent credentials and financial modeling system connections. Define contract risk thresholds Prerequisites Contract management system or data source; OpenAI API key; negotiation agent access Use Cases Corporate legal departments automating contract risk assessment across portfolios Customization Adjust contract analysis criteria and risk thresholds Benefits Eliminates manual contract review, identifies hidden risks automatically

🌟 AI-05: CCO Customer Success Team - Multi-Agent AI Workflow 📋 Overview Transform your customer success operations with this comprehensive AI-powered workflow featuring a strategic Chief Customer Officer (CCO) agent and six specialized customer success agents. This multi-agent system handles everything from onboarding to retention, ensuring maximum customer satisfaction and revenue expansion. 🔗 Links: YouTube Channel**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Website**: https://nofluff.online ⚙️ How It Works Customer Success Request: Chat interface receives requests like "Create a comprehensive onboarding program for enterprise customers" CCO Strategic Analysis: O3-powered CCO agent analyzes customer lifecycle and determines optimal success strategy Specialist Delegation: Work distributed to 6 specialized agents for execution Comprehensive Output: Integrated customer success deliverables with actionable recommendations 👥 Meet Your AI Customer Success Team | Agent | Specialization | Model | Primary Output | |-------|----------------|-------|---------------| | 🌟 CCO Agent | Customer success strategy & retention oversight | O3 | Strategic customer success planning | | 🚀 Customer Onboarding Specialist | Onboarding flows, welcome sequences, setup guides | GPT-4.1-mini | Onboarding programs | | 🆘 Customer Support Specialist | Support workflows, troubleshooting, help documentation | GPT-4.1-mini | Support systems | | 💊 Customer Health Analyst | Health scoring, risk identification, usage analytics | GPT-4.1-mini | Health assessments | | 📈 Upsell & Expansion Specialist | Growth opportunities, expansion strategies, upgrade paths | GPT-4.1-mini | Expansion plans | | 🎓 Customer Training Specialist | Training programs, certification courses, skill development | GPT-4.1-mini | Training curricula | | 🔄 Retention & Loyalty Specialist | Churn prevention, loyalty programs, renewal strategies | GPT-4.1-mini | Retention campaigns | 💡 Use Cases Complete Onboarding Programs**: Welcome sequences → Setup guides → Success milestones Customer Health Monitoring**: Usage tracking → Risk identification → Intervention strategies Expansion Revenue**: Account analysis → Upsell opportunities → Growth planning Support Excellence**: Knowledge bases → Workflow automation → Response optimization Training & Certification**: Learning paths → Skill assessments → Certification programs Retention Campaigns**: Churn prediction → Win-back strategies → Loyalty building 🎯 Key Benefits Proactive Success Management**: Identify and address customer needs before they become issues Revenue Expansion**: Systematic approach to identifying and capturing growth opportunities Operational Efficiency**: Streamlined processes for onboarding, support, and retention Data-Driven Insights**: Customer health scoring and predictive analytics Scalable Training**: Automated customer education and certification programs 💸 Cost Optimization Strategy O3 for CCO**: High-level customer success strategy and complex relationship management GPT-4.1-mini for Specialists**: 90% cost reduction for execution tasks Parallel Processing**: Multiple customer success workstreams handled simultaneously Template Reuse**: Proven customer success frameworks and best practices 🏗️ Building Blocks Approach This workflow provides foundational customer success components that you should customize: Adjust agent prompts** to match your industry, product, and customer segments Add relevant tools** like CRM integrations, analytics platforms, and communication systems Customize outputs** to align with your customer success methodology and KPIs Integrate workflows** with your existing customer success tech stack 🏷️ Tags #CustomerSuccess #CustomerExperience #ChurnPrevention #CustomerOnboarding #CustomerRetention #RevenueExpansion #CustomerHealth #CustomerSupport #CustomerTraining #LoyaltyPrograms #CustomerAnalytics #n8n #OpenAI #MultiAgentWorkflow #CustomerSuccessOps #CSMAutomation

💬 Conversational Calendar Bot for Telegram This workflow creates an AI chatbot on Telegram that intelligently manages your Google Calendar using natural language. It even checks for conflicts before scheduling! AI Models: Anthropic Claude 3.5 Haiku (Primary) & OpenAI GPT-4.1-mini (Fallback) How It Works Listen 👂: Triggered by a message in your Telegram chat. Understand 🧠: An AI Agent extracts the event details (title, date, time). Check 🧐: It first checks Google Calendar for any conflicting events. Decide ✅: If the slot is free, it creates the event. If not, it asks you for a new time. Confirm 👍: Sends a final confirmation message back to you. Nodes Used Telegram Trigger LangChain Agent Anthropic & OpenAI Models Google Calendar & Telegram Tools Setup Credentials: Add API keys for Telegram, Google Calendar, Anthropic, and OpenAI. Configure Nodes: Telegram Trigger: Add your specific Chat ID. Google Calendar Nodes ("Create" & "Get"): Select your calendar from the dropdown list. Example Usage To create a timed event: 🗓️ "Add an appointment to pick up graduation certificates on July 17th at 9 AM" To create an all-day event: PASSPORT "Remind me to renew my passport on August 20th"

Automate Market Problem Discovery from Reddit with OpenAI Who’s it for This workflow is perfect for entrepreneurs, startup founders, product managers, researchers, and market analysts who want to automatically discover and analyze real market problems from online discussions. While this example focuses on identifying issues in the future of work and future of education, it can be fully adapted to detect any type of market pain point by changing the data sources and AI prompts. If you’re looking to automate market research, find customer pain points, or detect unmet needs in your industry, this template is for you. What it does This no-code n8n automation: Collects fresh discussions from Reddit (default: Teachers, Education, RemoteWork subreddits). Filters posts by engagement (more than 5 upvotes by default). Uses OpenAI GPT-4.1 to: Detect if a post describes a real market problem. Identify the underlying pain or unmet need. Suggest a practical, tech/AI-based solution. Score the problem’s Impact, Confidence, and Ease of prototyping (ICE framework). Saves results to Google Sheets for easy prioritization and action. This allows you to automate the detection of market opportunities without manually reading through hundreds of posts. How it works Schedule Trigger**: Runs the workflow at your preferred interval (daily, hourly, etc.). Reddit Nodes**: Pull posts from the targeted subreddits (you can replace them with any niche communities). Filter Node**: Keeps only posts with engagement above your threshold. OpenAI Node: Analyzes each post using a **User Prompt and System Prompt in English, returning structured JSON data. Google Sheets Node**: Stores all results with full scoring for later review and prioritization. Requirements Reddit OAuth2 API credentials. OpenAI API key. Google Sheets OAuth2 API credentials. A Google Sheet with these columns: SubReddit, Title, Content, Short Description, Detected Pain, Possible Solution, Impact, Confidence, Ease, URL, ICE Score How to customize Change the market focus**: Replace example subreddits with your own industry forums or communities. Adjust the filter criteria**: Modify the upvote threshold or other parameters. Edit the AI prompts**: Tailor them to detect specific types of problems (healthtech, fintech, sustainability, etc.). Integrate more sources**: Add Twitter, LinkedIn, or customer support logs for richer insights. 💡 With this automation, you can continuously monitor and capture market pain points, turning raw online discussions into actionable business opportunities.

AI-Enriched Cold Outreach: Research → Draft → QA → Write-back What this template does Automates cold email drafting from a lead list by: Enriching each lead with LinkedIn profile, LinkedIn company, and Crunchbase data Generating a personalized subject + body with Gemini Auto-reviewing with a Judge agent and writing back only APPROVED drafts to your Data Table Highlights Hands-off enrichment via RapidAPI; raw JSON stored back on each row Two-agent pattern: Creative Outreach Agent (draft) + Outreach Email Judge (QA) Structured outputs guaranteed by LangChain Structured Output Parsers Data Table–native: reads “unprocessed” rows, writes results to the same row Async polling with Wait nodes for scraper task results How it works (flow) Trigger: Manual (replace with Cron if needed) Fetch leads: Data Table “Get row(s)” filters rows where email_subject is empty (pending) Loop: Split in Batches iterates rows Enrichment (runs in parallel): LinkedIn profile: HTTP (company_url) → Wait → Results → Data Table update → linkedin_profile_scrape LinkedIn company: HTTP (company_url) → Wait → Results → Data Table update → linkedin_company_scrape Crunchbase company: HTTP (url_search) → Wait → Results → Data Table update → crunchbase_company_scrape (All calls use host cold-outreach-enrichment-scraper with a RapidAPI key.) Draft (Gemini): “Agent One” composes a concise, personalized email using row fields + enrichment + ABOUT ME block. Structured Output Parser enforces: { "email_subject": "text", "email_content": "text" } Prep for QA: “Email Context” maps email_subject, email_content, and email for the judge. QA (Judge): “Judge Agent” returns APPROVED or REVISE (brief feedback allowed). Route: If APPROVED → Data Table “Update row(s)” writes email_subject + email_body (a.k.a. email_content) back to the row. If REVISE → Skipped; loop continues. Required setup Data Table: “email_linkedin_list” (or your own) with at least: email, First_name, Last_name, Title, Location, Company_Name, Company_site, Linkedin_URL, company_linkedin (if used), Crunchbase_URL, email_subject, email_body, linkedin_profile_scrape, linkedin_company_scrape, crunchbase_company_scrape (string fields for JSON). Credentials: RapidAPI key for cold-outreach-enrichment-scraper (store securely as credential, not hardcoded) Google Gemini (PaLM) API configured in the Google Gemini Chat Model node ABOUT ME block: Replace the sample persona (James / CEO / Company Sample / AI Automations) with your own. Nodes used Data Table** HTTP Request:** AI Agent:** Google Gemini Chat Model** Split in Batches:** Main Loop Set:** RapidAPI-Key Customization ideas Process flags:** Add email_generated_at or processed boolean to prevent reprocessing. Human-in-the-loop:** Send drafts to Slack/Email for spot check before write-back. Delivery:** After approval, optionally email the draft to the sender for review. Quotas & costs RapidAPI: Multiple calls per row (three tasks + result polls). Gemini: Token usage for generator + judge per row. Tune batch size and schedule accordingly. Privacy & compliance You are scraping and storing person/company data. Ensure lawful basis, respect ToS, and minimize stored data.