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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 PeyrinDocument-Aware WhatsApp AI Bot for Customer Support Google Docs-Powered WhatsApp Support Agent 24/7 WhatsApp AI Assistant with Live Knowledge from Google Docs Description Template Smart WhatsApp AI Assistant Using Google Docs Help customers instantly on WhatsApp using a smart AI assistant that reads your company’s internal knowledge from a Google Doc in real time. Built for clubs, restaurants, agencies, or any business where clients ask questions based on a policy, FAQ, or services document. How it works Users send free-form questions to your WhatsApp Business number (e.g. “What are the gym rules?” or “Are you open today?”) The bot automatically reads your company’s internal Google Doc (policy, schedule, etc.) It merges the document content with today’s date and the user’s question to craft a custom AI prompt The AI (Gemini or ChatGPT) then replies back on WhatsApp using natural, helpful language All conversations are logged to Google Sheets for reporting or audit > Bonus: The AI even understands dates inside the document and compares them to today’s date — e.g. if your document says “Closed May 25 for 30 days,” it will say “We're currently closed until June 24. Set up steps 1. Connect your WhatsApp Cloud API account (Meta) 2. Add your Google account and grant access to the Doc containing your company info 3. Choose your AI model (ChatGPT/OpenAI or Gemini) 4. Paste your document ID into the Google Docs node 5. Connect your WhatsApp webhook to Meta (only takes 5 minutes) 6. Done — start receiving and answering customer questions! > Works best with free-tier OpenAI/Gemini, Google Docs, and Meta's Cloud API (no phone required). Everything is modular, extensible, and low-code. Customization Tips Change the Google Doc anytime to update answers — no retraining needed Add your logo and business name in the AI agent’s “System Prompt” Add fallback routes like “Escalate to human” if the bot can't help Clone for multiple brands by duplicating the workflow and swapping in new docs Need Help Setting It Up? If you'd like help connecting your WhatsApp Business API, setting up Google Docs access, or customizing this AI assistant for your business or clients… I offer setup, branding, and customization services: WhatsApp Cloud API setup & verification Google OAuth & Doc structure guidance AI model configuration (OpenAI / Gemini) Branding & prompt tone customization Logging, reporting, and escalation logic Just send a message via: Email: tharwat.elsayed2000@gmail.com WhatsApp: +20 106 180 3236
by Tharwat MohamedWho this is for This workflow is for digital marketing agencies or sales teams who want to automatically find business leads based on industry & location, gather their contact details, and send personalized cold emails — all from one form submission. --- What this workflow does This workflow starts every time someone submits the Lead Machine Form. It then: Scrapes business data (company name, website, phone, address, category) using Apify based on business type & location. Extracts the best email address from each business website using Google Gemini AI. Stores valid leads in Google Sheets. Generates cold email content (subject + body) with AI based on your preferred tone (Friendly, Professional, Simple). Sends the cold email via Gmail. Updates the sheet with send status & timestamp. --- Setup To set this workflow up: 1. Form Trigger – Customize the “Lead Machine” form fields if needed (Business Type, Location, Lead Number, Email Style). 2. Apify API – Add your Apify Actor Endpoint URL in the HTTP Request node. 3. Google Gemini – Add credentials for extracting email addresses. 4. Google Sheets – Connect your sheet for storing leads & email status. 5. OpenAI – Add your credentials for cold email generation. 6. Gmail – Connect your Gmail account for sending cold emails. --- How to customize this workflow to your needs Change the AI email prompt to reflect your brand’s voice and offer. Add filters to only target leads that meet specific criteria (e.g., website must exist, email must be verified). Modify the Google Sheets structure to track extra info like “Follow-up Date” or “Lead Source”. Switch Gmail to another email provider if preferred. ---
by Rakin JakariaHow 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 PeyrinTelegram 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 OlusolaDescription This workflow automates the process of scraping the latest discussions from HackerNews, transforming raw threads into human readable content using Google Gemini, and exporting the final content into a well-formatted Google Doc. Overview This n8n workflow is responsible for extracting trending posts from the HackerNews API. It loops through each item, performs HTTP data extraction, utilizes Google Gemini to generate human-readable insights, and then exports the enriched content into Google Docs for distribution, archiving, or content creation. Who this workflow is for Tech Newsletter Writers: Automate the collection and summarization of trending HackerNews posts for inclusion in weekly or daily newsletters. Content Creators & Bloggers: Quickly generate structured summaries and insights from HackerNews threads to use as inspiration or supporting content for blog posts, videos, or social media. Startup Founders & Product Builders: Monitor HackerNews for discussions relevant to your niche or competitors, and keep a pulse on the community’s opinions. Investors & Analysts: Surface early signals from the tech ecosystem by identifying what’s trending and how the community is reacting. Researchers & Students: Analyze popular discussions and emerging trends in technology, programming, and startups—enriched with AI-generated insights. Digital Agencies & Consultants: Offer HackerNews monitoring and insight reports as a value-added service to clients interested in the tech space. Tools Used n8n: The core automation engine that manages the trigger, transformation, and export. HackerNews API: Provides access to trending or new HN posts. Google Gemini: Enriches HackerNews content with structured insights and human-like summaries. Google Docs: Automatically creates and updates a document with the enriched content, ready for sharing or publishing. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Set Up HackerNews Source: Choose whether to use the HN API (via HTTP Request node) or RSS Feed node. Configure Gemini API: Add your Google Gemini API key and design the prompt to extract pros/cons, key themes, or insights. Set Up Google Docs Integration: Connect your Google account and configure the Google Docs node to create/update a document. Test and Deploy: Run a test job to ensure data flows correctly and outputs are formatted as expected. Use Cases Tech Newsletter Authors: Generate ready-to-use summaries of trending HackerNews threads. Startup Founders: Stay informed on key discussions, product launches, and community feedback. Investors & Analysts: Spot early trends, technical insights, and startup momentum directly from HN. Researchers: Track community reactions to new technologies or frameworks. Content Creators: Use the enriched data to spark blog posts, YouTube scripts, or LinkedIn updates. Connect with Me Email: ranjancse@gmail.com LinkedIn: https://www.linkedin.com/in/ranjan-dailata/ Get Bright Data: Bright Data (Supports free workflows with a small commission) #n8n #automation #hackernews #contentcuration #aiwriting #geminiapi #googlegemini #techtrends #newsletterautomation #googleworkspace #rssautomation #nocode #structureddata #webscraping #contentautomation #hninsights #aiworkflow #googleintegration #webmonitoring #hnnews #aiassistant #gdocs #automationtools #gptlike #geminiwriter
by Ranjan DailataThis automation template turns any long video into multiple viral-ready short clips and auto-schedules them to TikTok, Instagram Reels, and YouTube Shorts. It works with both vertical and horizontal inputs and respects the original input resolution (no unnecessary upscaling), cropping or letterboxing intelligently when needed. The workflow automatically extracts between 3 and 6 clips (based on video length and the most engaging segments) and schedules one short per consecutive day—e.g., 3 clips → the next 3 days, 6 clips → the next 6 days. Note: This workflow uses OpenAI Whisper for word-level transcription, Google’s Gemini for clip selection and metadata, and Upload-Post’s FFmpeg API for GPU-accelerated cutting/cropping and social scheduling. You can use the same Upload-Post API token for both FFmpeg jobs and publishing uploads. Upload-Post also offers a generous free trial with no credit card required. Who Is This For? Creators & Editors: Batch-convert long talks/podcasts into daily Shorts/Reels/TikToks. Agencies & Social Teams: Turn webinars/interviews into a reliable short-form stream. Brands & Founders: Maintain a steady posting cadence with minimal hands-on editing. What Problem Does This Workflow Solve? Manual clipping is slow and inconsistent. This workflow: Finds Hooks Automatically: AI picks 3–6 high-retention segments from transcript + timestamps (count scales with video length/quality). Cuts Cleanly: Absolute-second FFmpeg timing to avoid mid-word cuts. Vertical & Horizontal Friendly: Handles both orientations and respects source resolution. Schedules for You: Posts one clip per day on consecutive days. How It Works 1. Form Upload: Submit your long video. 2. Audio Extraction: FFmpeg job extracts audio for accurate ASR. 3. Whisper Transcription: Word-level timestamps enable precise clipping. 4. AI Clip Mining (Gemini): Detects 3–6 “viral” moments (15–60s) and generates titles/descriptions. 5. Cut & Crop (FFmpeg): GPU pipeline produces clean clips; preserves input resolution/orientation when possible and crops/pads appropriately for target platforms. 6. Status & Download: Polls job status and retrieves the final clips. 7. Auto-Scheduling (Consecutive Days): Schedules one short per day starting tomorrow, for as many days as clips were produced (e.g., 3 clips → 3 days, 6 clips → 6 days) at a configurable time (default 20:00 Europe/Madrid). Setup 1. OpenAI (Whisper): Add your OpenAI API credentials. 2. Google Gemini: Add Gemini credentials used by the AI Agent node. 3. Upload-Post (free trial no credit card required): Generate your api token https://app.upload-post.com/ connect your social media accounts and add your API token credentials in n8n (same token works for FFmpeg jobs and publishing). 4. Scheduling: Adjust posting time/intervals and timezone (Europe/Madrid by default). 5. Metadata Mapping: Titles/descriptions are auto-generated per platform; tweak as needed. Requirements Accounts: n8n, OpenAI, Google (Gemini), Upload-Post, and social platform connections. API Keys: OpenAI token, Gemini credentials, Upload-Post token. Budget: Whisper + Gemini inference + FFmpeg compute + optional posting costs. Features Word-Accurate Cuts: Absolute-second timecodes with subtle pre/post-roll. Orientation-Aware: Supports vertical and horizontal inputs; preserves source resolution where possible. Platform-Optimized Output: 9:16-ready delivery with smart crop/pad behavior. Consecutive-Day Scheduler: 3–6 clips → 3–6 consecutive posting days, automatically. Retry & Polling: Built-in waits and status checks for robust processing. Modular: Swap models, adjust clip count/length, or add/remove platforms quickly. Turn long-form video into a consistent sequence of Shorts/Reels/TikToks—automatically, day after day, while respecting your source resolution.
by Juan Carlos Cavero GraciaYoutube 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 iamvaarAI-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 RafaelWho it's for This workflow is for professionals and small business owners who receive a high volume of emails and want to automate triage, labeling, and draft reply generation — without losing the human touch before sending. How it works 1. A Gmail trigger polls the inbox every minute for new unread emails and retrieves the current date. 2. The full email message is fetched, and any existing processing labels are stripped from the thread. 3. A Gemini 2.5 Pro AI Agent reads the email (and the full thread via a Gmail Thread tool), checks Google Calendar for availability, then classifies the email into one of six categories (Urgent, Reply, Read, Notification, Newsletter, Invoice) and drafts an HTML reply when needed. 4. A Switch node routes the output: emails requiring a reply (Urgent or Reply) pass through a JavaScript node that appends an HTML signature before saving the message as a Gmail draft. 5. All paths converge to fetch the matching Gmail label, filter for validity, apply it to the thread, and mark the message as unread so it surfaces for human review. How to set up [ ] Connect a Gmail OAuth2 credential to all Gmail nodes (trigger, fetch, remove label, draft, label, mark unread) [ ] Connect a Google Gemini (PaLM) API credential to the Gemini Chat Model node [ ] Connect a Google Calendar OAuth2 credential to the Google Calendar Tool node [ ] Configure the Gmail Trigger label/filter to match your inbox setup [ ] Update the label IDs in Remove Label from Thread, Get label for response, and Labelliser to match your Gmail labels [ ] Customize the HTML signature in the Build HTML Signature code node Requirements Gmail account with OAuth2 access Google Gemini (PaLM) API key Google Calendar account How to customize Adjust the AI Agent's system prompt to change tone, add new label categories, or modify the reply structure. Extend the Switch node with additional branches (e.g., forward to a team member, archive automatically, create a CRM task). Replace the Gmail draft step with a direct send for fully automated responses on low-risk categories like Notifications.
by Allan VaccariziThis 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)Daily Crypto AI Market Insight to Telegram This workflow generates a daily AI-powered crypto market insight and sends it to Telegram using Binance public market data, the Crypto Fear & Greed Index, and Google Gemini. It fetches BTC/USDT daily OHLCV data, calculates technical indicators, builds a structured analysis payload, asks Gemini for a buy/hold/sell confidence breakdown, and delivers the result as a clean Telegram report. It is useful for traders, builders, and crypto enthusiasts who want an automated daily technical summary without manually checking charts. Common use cases: Send a daily BTC market insight to your Telegram Monitor crypto technical indicators automatically Build a personal AI crypto analyst bot Create a lightweight daily trading signal workflow Learn how to combine market data, technical indicators, LLMs, and Telegram in n8n How it works Starts from a Schedule Trigger, which you can customize Sets the trading pair, for example BTCUSDT Fetches 300 daily OHLCV candles from Binance public API Normalizes Binance candle data into readable fields Fetches the latest market price and merges it into the latest candle Fetches the Crypto Fear & Greed Index from Alternative.me Calculates EMA(20), EMA(50), EMA(100), RSI(14), MACD histogram, ADX(14), +DI, and -DI Builds a structured technical payload Sends the payload to Google Gemini Parses Gemini’s response into structured JSON Formats the result into a Telegram message Sends the AI-generated insight to Telegram Setup steps Choose your trading pair in the Set Trading Pair node Connect your Google Gemini credentials Connect your Telegram credentials Set your Telegram chat ID in the Telegram node Adjust the Schedule Trigger if you want a different run time Test the workflow manually Activate the workflow Notes This workflow uses Binance public API data and does not require a Binance API key. The AI insight is generated only from the provided technical payload and should not be treated as financial advice. Need Help? Have questions or want to connect? Reach me on LinkedIn.
by Atha Ahsan Xavier Haris