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How it works This template launches your very first AI Agent —an AI-powered chatbot that can do more than just talk— it can take action using tools. Think of an AI Agent as a smart assistant, and the tools are the apps on its phone. By connecting it to other nodes, you give your agent the ability to interact with real-world data and services, like checking the weather, fetching news, or even sending emails on your behalf. This workflow is designed to be the perfect starting point: The Chat Interface: A Chat Trigger node provides a simple, clean interface for you to talk to your agent. The Brains: The AI Agent node receives your messages, intelligently decides which tool to use (if any), and formulates a helpful response. Its personality and instructions are fully customizable in the "System Message". The Language Model: It uses Google Gemini to power its reasoning and conversation skills. The Tools: It comes pre-equipped with two tools to demonstrate its capabilities: 1. Get Weather: Fetches real-time weather forecasts. 2. Get News: Reads any RSS feed to get the latest headlines. The Memory: A Conversation Memory node allows the agent to remember the last few messages, enabling natural, follow-up conversations. Set up steps Setup time: ~2 minutes You only need one thing to get started: a free Google AI API key. 1. Get Your Google AI API Key: Visit Google AI Studio at aistudio.google.com/app/apikey. Click "Create API key in new project" and copy the key that appears. 2. Add Your Credential in n8n: On the workflow canvas, go to the Connect your model (Google Gemini) node. Click the Credential dropdown and select + Create New Credential. Paste your API key into the API Key field and click Save. 3. Start Chatting! Go to the Example Chat node. Click the "Open Chat" button in its parameter panel. Try asking it one of the example questions, like: "What's the weather in Paris?" or "Get me the latest tech news."* That's it! You now have a fully functional AI Agent. Try adding more tools (like Gmail or Google Calendar) to make it even more powerful.
by Lucas PeyrinHow it works This template is a complete, hands-on tutorial that lets you build and interact with your very first AI Agent. Think of an AI Agent as a standard AI chatbot with superpowers. The agent doesn't just talk; it can use tools to perform actions and find information in real-time. This workflow is designed to show you exactly how that works. 1. The Chat Interface (Chat Trigger): This is your window to the agent. It's a fully styled, public-facing chat window where you can have a conversation. 2. The Brain (AI Agent Node): This is the core of the operation. It takes your message, understands your intent, and intelligently decides which "superpower" (or tool) it needs to use to answer your request. The agent's personality and instructions are defined in its extensive system prompt. 3. The Tools (Tool Nodes): These are the agent's superpowers. We've included a variety of useful and fun tools to showcase its capabilities: Get a random joke. Search Wikipedia for a summary of any topic. Calculate a future date. Generate a secure password. Calculate a monthly loan payment. Fetch the latest articles from the n8n blog. 4. The Memory (Memory Node): This gives the agent a short-term memory, allowing it to remember the last few messages in your conversation for better context. When you send a message, the agent's brain analyzes it, picks the right tool for the job, executes it, and then formulates a helpful response based on the tool's output. Set up steps Setup time: ~3 minutes This template is nearly ready to go out of the box. You just need to provide the AI's "brain." 1. Configure Credentials: This workflow requires an API key for an AI model. Make sure you have credentials set up in your n8n instance for either Google AI (Gemini) or OpenAI. 2. Choose Your AI Brain (LLM): By default, the workflow uses the Google Gemini node. If you have Google AI credentials, you're all set! If you prefer to use OpenAI, simply disable the Gemini node and enable the OpenAI node. You only need one active LLM node. Make sure it is connected to the Agent parent node. 3. Explore the Tools: Take a moment to look at the different tool nodes connected to the Your First AI Agent node. This is where the agent gets its abilities! You can add, remove, or modify these to create your own custom agent. 4. Activate and Test! Activate the workflow. Open the public URL for the Example Chat Window node (you can copy it from the node's panel). Start chatting! Try asking it things like: "Tell me a joke." "What is n8n?" "Generate a 16-character password for me." "What are the latest posts on the n8n blog?" "What is the monthly payment for a $300,000 loan at 5% interest over 30 years?"
by Lucas PeyrinWho’s it for This template is designed for anyone who wants to use Telegram as a personal AI assistant hub. If you often juggle tasks, emails, calendars, and expenses across multiple tools, this workflow consolidates everything into one seamless AI-powered agent. What it does Jarvis listens to your Telegram messages (text or audio) and processes them with OpenAI. Based on your request, it can: Manage tasks (create, complete, or delete) Handle calendar events (schedule, reschedule, or check availability) Send, draft, or fetch emails with Gmail Retrieve Google Contacts Log and track expenses All responses are returned directly to Telegram, giving you a unified command center. How to set up 1. Clone this template into your n8n workspace. 2. Connect your accounts (Telegram, Gmail, Google Calendar, Contacts, etc.). 3. Add your OpenAI API key in the Credentials section. 4. Test by sending a Telegram message like “Create a meeting tomorrow at 3pm” or “Add expense $50 for lunch.” or "Draft a reply with a project proposal to that email from Steve" Requirements n8n instance (cloud or self-hosted) Telegram Bot API credentials Gmail, Google Calendar, and Google Contacts credentials (optional, if using those features) OpenAI API key ElevenLabs API Key (optional, if you need audio note support) How to customize Swap Gmail with another email provider by replacing the Gmail MCP node. Add additional MCP integrations (e.g., Notion, Slack, CRM tools). Adjust memory length to control how much context Jarvis remembers. With this template, you can transform Telegram into your all-in-one AI assistant, simplifying workflows and saving hours every week.
by Jitesh DugarTelegram Nutrition AI Assistant (Alternative to Cal AI App) > AI-powered nutrition assistant for Telegram — log meals, set goals, and get personalized daily reports with Google Sheets integration. Description This n8n template creates a Telegram-based Nutrition AI Assistant designed as an open-source alternative to the Cal AI mobile app. It allows users to interact with an AI agent via text, voice, or images to track meals, calculate macros, and monitor nutrition goals directly from Telegram. The system integrates Google Sheets as the database, handling both user profiles and meal logs, while leveraging Gemini AI for natural conversation, food recognition, and daily progress reports. Key Features Multi-input support: Text, voice messages (transcribed), and food images (AI analysis). Macro calculation: Automatic estimation of calories, proteins, carbs, and fats. User-friendly registration: Simple onboarding without storing personal health data (no weight/height required). Goal tracking: Users can set and update calorie and protein targets. Daily reports: Personalized progress messages with visual progress bars. Google Sheets integration: Profile table for user targets. Meals table for food logs. Advanced n8n nodes: Includes use of Merge, Subworkflow, and Code nodes for data processing and report generation. Acknowledgment Inspired by the Cal AI concept — this template demonstrates how to reproduce its main functionality with n8n, Telegram, and AI agents as a flexible, open-source automation workflow. Tags telegram ai-assistant nutrition meal-tracking google-sheets food-logging voice-transcription image-analysis daily-reports n8n-template merge-node subworkflow-node code-node telegram-trigger google-gemini Use Case Use this template if you want to: Log meals using text, images, or voice messages. Track nutrition goals (calories, proteins) with daily progress updates. Provide a chat-based nutrition assistant without building a full app. Store structured nutrition data in Google Sheets for easy access and analysis. Example User Interactions User sends a photo of a meal → AI analyzes the food and logs calories/macros. User sends a voice message → AI transcribes and logs the meal. User types “report” → AI returns a daily nutrition summary with progress bars. User says “update my protein goal” → AI updates profile in Google Sheets. Required Credentials Telegram Bot API (Bot Token) Google Sheets API credentials AI Provider API (Google Gemini or compatible LLM) Setup Instructions 1. Create two Google Sheets tables: Profile: User_ID, Name, Calories_target, Protein_target Meals: User_ID, Date, Meal_description, Calories, Proteins, Carbs, Fats 2. Configure the Telegram Trigger with your bot token. 3. Connect your AI provider credentials (Gemini recommended). 4. Connect Google Sheets with your credentials. 5. ▶ Deploy the workflow in n8n. 6. Start interacting with your nutrition assistant via Telegram. Extra Notes Green section: Handles Telegram trigger and user check. Red section: Registers new users and sets goals. Blue section: Processes text, voice, and images. Yellow section: Generates nutrition reports. Purple section: Main AI agent controlling tools and logic. --- Need Assistance? If you’d like help customizing or extending this workflow, feel free to reach out: Email: johnsilva11031@gmail.com LinkedIn: John Alejandro Silva Rodríguez
by John Alejandro SIlvaMaster Your First AI Email Agent with Smart Fallback! Welcome to your hands-on guide for building a resilient, intelligent email support system in n8n! This workflow is specifically designed as an educational tool to help you understand advanced AI automation concepts in a practical, easy-to-follow way. --- What You'll Learn & Build: This powerful template enables you to create an automated email support agent that: Monitors Gmail for new customer inquiries in real-time. Processes requests using a primary AI model (Google Gemini) for efficiency. Intelligently falls back to a secondary AI model (OpenAI GPT) if the primary model fails or for more complex queries, ensuring robust reliability. Generates personalized and helpful replies automatically. Logs every interaction meticulously to a Google Sheet for easy tracking and analysis. --- Why a Fallback Model is Game-Changing (and Why You Should Learn It): Unmatched Reliability (99.9% Uptime): If one AI service experiences an outage or rate limits, your automation seamlessly switches to another, ensuring no customer email goes unanswered. Cost Optimization: Leverage more affordable models (like Gemini) for standard queries, reserving premium models (like GPT) only when truly needed, significantly reducing your API costs. Superior Quality Assurance: Get the best of both worlds – the speed of cost-effective models combined with the accuracy of more powerful ones for complex scenarios. Real-World Application: This isn't just theory; it's a critical pattern for building resilient, production-ready AI systems. --- Perfect for Beginners & Aspiring Automators: Simple Setup: With drag-and-drop design and pre-built integrations, you can get this workflow running with minimal configuration. Just add your API keys! Clear Educational Value: Learn core concepts like AI model orchestration strategies, customer service automation best practices, and multi-model AI implementation patterns. Immediate Results: See your AI agent in action, responding to emails and logging data within minutes of setup. --- Getting Started Checklist: To use this workflow, you'll need: A Gmail account with API access enabled. A Google Sheets document created for logging. A Gemini API key (your primary AI model). An OpenAI API key (your fallback AI model). An n8n instance (cloud or desktop). --- Embark on your journey to building intelligent, resilient automation systems today!
by David OlusolaYoutube Explanation: https://youtu.be/KgmNiV7SwkU This n8n workflow is designed to automate the initial intake and scheduling for a law firm. It's split into two main parts: 1. New Inquiry Handling: Kicks off when a potential client fills out a JotForm, saves their data, and sends them an initial welcome message on WhatsApp. 2. Appointment Scheduling: Activates when the client replies on WhatsApp, allowing an AI agent to chat with them to schedule a consultation. Here’s a detailed breakdown of the prerequisites and each node. ** Prerequisites Before building this workflow, you'll need accounts and some setup for each of the following services: JotForm JotForm Account: You need an active JotForm account. A Published Form: Create a form with the exact fields used in the workflow: Full Name, Email Address, Phone Number, I am a..., Legal Service of Interest, Brief Message, and How Did You Hear About Us?. API Credentials: Generate API keys from your JotForm account settings to connect it with n8n. Google Google Account: To use Google Sheets and Google Calendar. Google Sheet: Create a new sheet named "Law Client Enquiries". The first row must have these exact headers: Full Name, Email Address, Phone Number, client type, Legal Service of Interest, Brief Message, How Did You Hear About Us?. Google Calendar: An active calendar to manage appointments. Google Cloud Project: Service Account Credentials (for Sheets): In the Google Cloud Console, create a service account, generate JSON key credentials, and enable the Google Sheets API. You must then share your Google Sheet with the service account's email address (e.g., automation-bot@your-project.iam.gserviceaccount.com). OAuth Credentials (for Calendar): Create OAuth 2.0 Client ID credentials to allow n8n to access your calendar on your behalf. You'll need to enable the Google Calendar API. Gemini API Key: Enable the Vertex AI API in your Google Cloud project and generate an API key to use the Google Gemini models. WhatsApp Meta Business Account: Required to use the WhatsApp Business Platform. WhatsApp Business Platform Account: You need to set up a business account and connect a phone number to it. This is different from the regular WhatsApp or WhatsApp Business app. API Credentials: Get the necessary access tokens and IDs from your Meta for Developers dashboard to connect your business number to n8n. PostgreSQL Database A running PostgreSQL instance: This can be hosted anywhere (e.g., AWS, DigitalOcean, Supabase). The AI agent needs it to store and retrieve conversation history. Database Credentials: You'll need the host, port, user, password, and database name to connect n8n to it. Node-by-Node Explanation The workflow is divided into two distinct logical flows. Flow 1: New Client Intake from JotForm This part triggers when a new client submits your form. 1. JotForm Trigger What it does: This is the starting point. It automatically runs the workflow whenever a new submission is received for the specified JotForm (Form ID: 252801824783057). Prerequisites: A JotForm account and a created form. 2. Append or update row in sheet (Google Sheets) What it does: It takes the data from the JotForm submission and adds it to your "Law Client Enquiries" Google Sheet. How it works: It uses the appendOrUpdate operation. It tries to find a row where the "Email Address" column matches the email from the form. If it finds a match, it updates that row; otherwise, it appends a new row at the bottom. Prerequisites: A Google Sheet with the correct headers, shared with your service account. 3. AI Agent What it does: This node crafts the initial welcome message to be sent to the client. How it works: It uses a detailed prompt that defines a persona ("Alex," a legal intake assistant) and instructs the AI to generate a professional WhatsApp message. It dynamically inserts the client's name and service of interest from the Google Sheet data into the prompt. Connected Node: It's powered by the Google Gemini Chat Model. 4. Send message (WhatsApp) What it does: It sends the message generated by the AI Agent to the client. How it works: It takes the client's phone number from the data (Phone Number column) and the AI-generated text (output from the AI Agent node) to send the message via the WhatsApp Business API. Prerequisites: A configured WhatsApp Business Platform account. --- Flow 2: AI-Powered Scheduling via WhatsApp This part triggers when the client replies to the initial message. 1. WhatsApp Trigger What it does: This node listens for incoming messages on your business's WhatsApp number. When a client replies, it starts this part of the workflow. Prerequisites: A configured WhatsApp Business Platform account. 2. If node What it does: It acts as a simple filter. It checks if the incoming message text is empty. If it is (e.g., a status update), the workflow stops. If it contains text, it proceeds to the AI agent. 3. AI Agent1 What it does: This is the main conversational brain for scheduling. It handles the back-and-forth chat with the client. How it works: Its prompt is highly detailed, instructing it to act as "Alex" and follow a strict procedure for scheduling. It has access to several "tools" to perform actions. Connected Nodes: Google Gemini Chat Model1: The language model that does the thinking. Postgres Chat Memory: Remembers the conversation history with a specific user (keyed by their WhatsApp ID), so the user doesn't have to repeat themselves. Tools: Know about the user enquiry, GET MANY EVENTS..., and Create an event. 4. AI Agent Tools (What the AI can do) Know about the user enquiry (Google Sheets Tool): When the AI needs to know who it's talking to, it uses this tool. It takes the user's phone number and looks up their original enquiry details in the "Law Client Enquiries" sheet. GET MANY EVENTS... (Google Calendar Tool): When a client suggests a date, the AI uses this tool to check your Google Calendar for any existing events on that day to see if you're free. Create an event (Google Calendar Tool): Once a time is agreed upon, the AI uses this tool to create the event in your Google Calendar, adding the client as an attendee. 5. Send message1 (WhatsApp) What it does: Sends the AI's response back to the client. This could be a confirmation that the meeting is booked, a question asking for their email, or a suggestion for a different time if the requested slot is busy. How it works: It sends the output text from AI Agent1 to the client's WhatsApp ID, continuing the conversation.
by iamvaarWho’s it for This template is built for WooCommerce store owners, eCommerce managers, and automation agencies who want to manage store operations directly from Telegram using an AI assistant. It’s ideal for users looking to save time, automate support, and access store data conversationally. How it works When a user sends a message via Telegram, the workflow triggers an AI agent that understands the request using a chat model with memory. Based on the intent, the agent executes the appropriate action such as retrieving orders, fetching product data, updating product information, logging data into Google Sheets, or sending email notifications. How to set up 1. Connect your Telegram bot credentials 2. Add your WooCommerce API keys 3. Connect Google Sheets for data storage 4. Connect your Gmail account 5. Configure your OpenRouter or OpenAI API key 6. Test the workflow via Telegram commands Requirements WooCommerce store with API access Telegram bot token Google Sheets account Gmail credentials OpenRouter or OpenAI API key How to customize You can expand this agent by adding tools like order creation, refund processing, CRM integrations, shipping updates, or advanced reporting. The AI prompt can also be modified to match your store operations.
by Nid AcademyAI-Enriched Cold Outreach: Research → Draft → QA → Write-back ============================================================ What this template does ----------------------- Automates cold email drafting from a lead list by: 1. Enriching each lead with LinkedIn profile, LinkedIn company, and Crunchbase data 2. Generating a personalized subject + body with Gemini 3. 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) ------------------- 1. Trigger: Manual (replace with Cron if needed) 2. Fetch leads: Data Table “Get row(s)” filters rows where email_subject is empty (pending) 3. Loop: Split in Batches iterates rows 4. 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.) 5. Draft (Gemini): “Agent One” composes a concise, personalized email using row fields + enrichment + ABOUT ME block. Structured Output Parser enforces: ``json { "email_subject": "text", "email_content": "text" } ` 6. Prep for QA: “Email Context” maps email_subject, email_content, and email for the judge. 7. QA (Judge): “Judge Agent” returns APPROVED or REVISE (brief feedback allowed). 8. 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.
by Johnny RafaelThis n8n template automates the collection, storage, and summarization of technology news and discussions from the n8n Community and Reddit (r/n8n). If you like staying informed but want to reduce daily manual browsing distractions, this workflow is perfect for you. How it works User Intent Detection: The workflow receives your Telegram message and uses an AI Agent (powered by Gemini/Groq) to intelligently classify your intent (Search, Deep-dive, or Casual Chat). Multi-Platform Scraping: Automatically fetches the latest discussions, topics, and comments from the official n8n Community and Reddit via HTTP Requests. Smart Summarization: Extracts complex HTML content and uses the AI to provide concise overviews, or deep-dives into specific forum threads with full contextual history. Seamless Delivery: Formats the AI's response into clean, chunked Telegram messages (handling limits smoothly) and delivers it straight to your chat. Daily Pulse: A scheduled trigger automatically aggregates the hottest topics every morning to keep you updated. How to use 1. Connect your Telegram Bot account to n8n. 2. Connect your Google Gemini and Groq API credentials. 3. (Optional) Connect your MongoDB instance if you want to enable long-term persistent chat memory. 4. Update the Chat ID in the Telegram nodes to route the scheduled Daily Pulse directly to your personal account or group. 5. Activate the workflow and start messaging your new AI assistant. Requirements n8n Version: Built and tested on n8n 2.9.4+. (Note: You may encounter errors on older versions. It is highly recommended to update to the latest n8n version to use this workflow effectively). Telegram Bot token. Google Gemini & Groq API keys. (Optional) MongoDB connection string. Customizing this workflow Change the AI Model: Swap the Gemini or Groq nodes for OpenAI, Claude, or any other supported LLM. Expand the Sources: Duplicate the HTTP Request nodes and adjust the HTML extractors to monitor other platforms like Discord or StackOverflow. Adjust the Schedule: Prefer chat over daily emails? Change the Cron expression to receive weekly summaries or disable it entirely to rely purely on on-demand Telegram queries. --- About the Author Created by: Nguyen Thieu Toan (Jay Nguyen) Email: me@nguyenthieutoan.com Website: nguyenthieutoan.com Company: CEO/Founder of GenStaff (genstaff.net) - AI Staffing Solutions Socials (Facebook / X / LinkedIn): @nguyenthieutoan More templates: n8n.io/creators/nguyenthieutoan
by Nguyễn Thiệu Toàn (Jay Nguyen)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 1. Read seniors from Google Sheets (Senior_data) with: StudentID, Name, Program, Year, CompletedCourses. 2. AI Agent compares CompletedCourses to built-in requirements (per program) and computes Missing items + a short Summary. 3. 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
by Robert BreenDescription: Automate your entire supplier negotiation process with this AI-driven workflow that intelligently drafts, refines, and sends negotiation emails . Using advanced LLM reasoning and multi-angle strategies , it generates high-converting negotiation messages tailored to each supplier scenario. The workflow tracks replies, sends smart follow-ups , and logs outcomes automatically for full visibility. Perfect for procurement teams looking to reduce costs and eliminate manual back-and-forth communication . What This Template Does: Triggers when a new supplier entry is added to Google Sheets. Validates and structures supplier, product, and pricing data. Generates 3 AI-powered negotiation email drafts using different strategies. Selects the best-performing draft based on scoring logic. Refines the draft using AI self-critique for better tone and clarity. Sends the final negotiation email to the supplier via Gmail. Waits 24 hours and checks for supplier replies automatically. Detects whether a reply is received and routes the workflow accordingly. Sends an optimized follow-up email if no response is received. Logs negotiation details and outcomes in Notion. Updates Google Sheets with final status, pricing, and savings. Notifies the procurement team via Slack with results or retry alerts. Key Benefits: Fully autonomous negotiation process with zero manual effort AI-optimized messaging increases chances of better pricing Smart follow-ups ensure no supplier opportunity is missed Centralized tracking across Sheets, Notion, and Slack Data-driven decision making with scoring and insights Scalable procurement operations for high-volume supplier outreach Features: Google Sheets trigger-based workflow AI-powered negotiation using GPT-4o (multi-angle + self-critique) Automated email sending and reply detection via Gmail Intelligent retry logic using DPO-style optimization Notion logging for audit trails and reporting Slack alerts for real-time team notifications Built-in validation and structured data processing Requirements: Google Sheets account (for supplier data tracking) Gmail account (for sending and receiving emails) OpenAI API key (for AI-generated negotiation logic) Notion account (for logging negotiation outcomes) Slack account (for team notifications) Target Audience: Procurement and sourcing teams E-commerce and retail businesses managing suppliers Startups scaling vendor negotiations Automation agencies building AI-driven business workflows
by Rahul JoshiQuick Overview This workflow lets users manage Google Calendar by sending text or voice messages to a Zalo Official Account bot, transcribing voice notes with Google Gemini and using an OpenAI-powered agent to create, update, list, or delete events, then replying in Zalo with the result. How it works 1. Receives an incoming text or voice message through a Zalo Bot trigger. 2. Sends a typing indicator back to the Zalo chat and normalizes key message fields (chat ID, type, text, and voice URL). 3. If the message is a voice note, sends the audio URL to Google Gemini to transcribe it into text. 4. Sends the combined text/transcription to an OpenAI chat model agent that interprets the request in Vietnamese and decides whether to list, create, update, or delete a Google Calendar event. 5. Uses Google Calendar tools to get events and then create, update, or delete the targeted event based on the agent’s extracted parameters. 6. Sends the agent’s Markdown-formatted response back to the user in Zalo, and posts an error message to Zalo if the agent run fails. Setup 1. Install the community node package n8n-nodes-zalo-bot-official and restart n8n if required. 2. Connect your Zalo Bot API credentials and configure the Zalo webhook URL in your Zalo Official Account so incoming messages reach this workflow. 3. Add a Google Calendar OAuth2 credential and set the target calendar account (currently configured as toannguyen96vn@gmail.com) for all calendar operations. 4. Add a Google Gemini (PaLM) API credential for audio transcription and ensure voice messages include a reachable voice_url. 5. Add an OpenAI API credential, select the chat model you want to use (currently gpt-5-mini), and adjust the system prompt/tone if needed.
by Nguyễn Thiệu Toàn (Jay Nguyen)