Workflow Templates

Qualify and Call Back Inbound Leads with OpenAI, Bland AI, Airtable & SendGrid This n8n template demonstrates how to capture inbound leads from a form, qualify them with OpenAI, and route the hottest ones to a Bland AI voice agent that calls them back, books a meeting on Google Calendar, and confirms by email, all without a human touching the lead. Use cases are many: instant follow-up on paid-ad leads, voice qualification for high-ticket consulting inquiries, or replacing the "first response" SDR seat entirely! Good to know Each Bland AI call is billed per minute. The default max_duration in this template is 5 minutes; see Bland AI pricing for the current rate. OpenAI calls for qualification cost fractions of a cent per lead, but volume adds up; set a budget alert on your OpenAI account if you're running paid traffic. You can also use Claude. Outbound calling is regulated. Make sure you have consent on your form and check the rules for your country (TCPA in the US, PECR in the UK, etc.) before going live. How it works We capture the lead via a webhook; your form, quiz, or landing page posts the payload (name, email, phone, company, plus any qualification fields you collect). A code node normalises the payload, an IF node rejects anything missing required fields, and the lead is written to Airtable so you have a single source of truth. OpenAI is then used to qualify the lead. We give it the cleaned payload and ask it to return one of three next actions: nurture_email, priority_email, or ai_call. Low-intent leads get a SendGrid nurture email. Medium-intent leads get a priority email. High-intent leads continue down to the voice path. For the voice path, we pull free slots from Google Calendar, format them into a natural-speech sentence ("I have Tuesday at 2 or Thursday at 10…"), and POST to Bland AI with the script, the lead's number, and a callback URL. Bland AI calls the lead, runs the script, and posts the outcome back to the second webhook in this same workflow. If a slot was booked, we create the Google Calendar event, update the Airtable record, and send a SendGrid confirmation. If the call failed (no answer, declined, error), we update Airtable and send a priority follow-up email so a human can step in. How to use The webhook trigger is set up for a typical form payload, but feel free to swap it for a Typeform/Tally trigger, a Calendly cancellation, or any inbound source. Tune the prompt inside the AI Lead Qualification node to match your ICP; the routing logic only cares that the model returns one of the three action strings. Edit the voice script inside the Trigger AI Phone Call body to match your company name, agent name, and offer before going live. The Bland AI webhook field inside the request body must point to the production URL of the Call Outcome Webhook node in this same workflow so Bland can post back. Requirements OpenAI account for lead qualification Bland AI account for the outbound voice agent Airtable base with a Leads table SendGrid account for emails Google Calendar for availability and event creation Customising this workflow AI voice follow-up works for plenty of inbound flows beyond sales calls. Try it for booking demos, recovering abandoned checkout carts with a quick "is everything okay?" call, or as a re-engagement layer on stale leads in your CRM.

Quick Overview This workflow receives support messages via a webhook, normalizes payloads from Gmail, Zendesk, Intercom, and HelpScout, and uses Anthropic Claude to detect escalation signals and severity, then posts alerts to Slack and creates Linear tickets for actionable cases. How it works Receives an inbound support message via a POST webhook. Normalizes the incoming payload (Gmail, Zendesk, Intercom, HelpScout, or a raw test payload) into a consistent schema with customer details, subject, body text, and a source URL. Sends the normalized message to Anthropic Claude and parses the response into structured JSON containing escalation flags, severity, trigger phrases, a summary, and a suggested reply opening. Stops processing silently when the message is not an escalation (severity is none). Builds a formatted Slack alert and Linear issue payload, including SLA guidance, detected signals, and links back to the original conversation. Posts the escalation alert to a configured Slack channel. Creates a Linear ticket for critical, high, and medium severity escalations and sends a Slack DM to a manager for critical and high cases. Setup Add an Anthropic API credential for the Anthropic Chat Model node. Add a Slack OAuth2 credential, set the target channel (for example, #escalations), and set the manager’s Slack user ID for direct messages. Add a Linear OAuth2 credential and replace the placeholder Linear team ID used when creating tickets. Copy the webhook URL from the webhook trigger and configure Gmail/Zendesk/Intercom/HelpScout (or your custom source) to POST message payloads to it in one of the supported formats.

Who’s it for Teams that start their day in Slack and want a concise, automated summary of yesterday’s emails—ops leads, PMs, founders, and anyone handling busy inboxes without writing code. What it does / How it works Runs every morning at 08:00 (cron 0 0 8 * * ), fetches all emails received *yesterday, and routes the result: if none were found, it posts a polite “no emails” notice; if emails exist, it aggregates them and asks an AI agent to produce a structured digest, then formats and posts to your chosen Slack channel. The flow uses **Gmail → If → Aggregate (Item Lists) → AI Agent (OpenRouter model with structured output) → Code (Slack formatter) → Slack. A set of sticky notes on the canvas explains each step and required inputs. How to set up Connect Gmail (OAuth2) and keep the default date window (yesterday → today at 00:00). Connect Slack (OAuth2) and select your target channel. Add OpenRouter credentials and pick a compact model (e.g., gpt-4o-mini). Keep the provided structured-output schema and formatter code. Adjust the schedule/timezone if needed (the fallback message includes an Asia/Tokyo example). Paste this description into the yellow sticky note at the top of the canvas. Requirements Gmail & Slack accounts with appropriate scopes OpenRouter API key stored in Credentials (no hard-coded keys) n8n Cloud or self-host with LangChain agent nodes enabled How to customize the workflow Narrow Gmail results with label/search filters (e.g., from:, subject:). Change the digest sections or tone in the AI Agent system prompt. Swap the model for cost/quality needs and tweak temperature/max tokens. Localize dates/timezones in the formatter code and Slack messages. Branch the output to email, Google Docs, or Sheets for archival. Security & publishing tips Rename all nodes clearly, do not hardcode API keys, remove real channel IDs/emails before sharing, and group end-user variables in a Set (Fields) node. Keep the sticky notes—they’re mandatory for reviewers.

Description Who's it for This workflow is designed for developers, entrepreneurs, and startup enthusiasts who want personalized, AI-driven startup idea generation and analysis. Perfect for solo developers seeking side project inspiration, startup accelerators evaluating concepts, or anyone looking to validate business ideas with professional-grade analysis. How it works The workflow uses a three-stage Claude AI agent pipeline to create comprehensive startup analyses. The first agent generates innovative startup ideas based on your technical skills and preferences. The second agent acts as a venture capitalist, critically analyzing market viability, competition, and execution challenges. The third agent performs sentiment analysis and synthesizes a final recommendation with actionable next steps. How to set up Configure Anthropic API credentials for all three Claude AI model nodes Set up Gmail OAuth2 for email delivery Fill out the "My Information" node with your developer profile Update the recipient email address in the Gmail node Test with the manual trigger before enabling daily automation Requirements n8n account Anthropic API account for Claude AI access Gmail account with OAuth2 configured Basic understanding of developer skills and market preferences How to customize the workflow Modify the AI agent prompts to focus on specific industries or business models. Adjust temperature settings for different creativity levels. Add database storage to track idea history. Configure the form trigger for team-wide idea generation or integrate with Slack for automated sharing. Got a good idea? Visit my site https://techpoweredgrowth.com to get help getting to the next level Or reach out to luka.zivkovic@techpoweredgrowth.com

This workflow finds fresh Reddit posts that match your keywords, decides if they’re actually relevant to your brand, writes a short human-style reply using AI, posts it, and logs everything to Baserow. 💡Perfect for Lead gen without spam: drop helpful replies where your audience hangs out. Get discovered by AI surfaces (AI Overviews / SGE, AISEO/GSEO) via high-quality brand mentions. Customer support in the wild: answer troubleshooting threads fast. Community presence: steady, non-salesy contributions in niche subreddits. 🧠 What it does Searches Reddit for your keyword query on a schedule (e.g., every 30 min) Checks Baserow first so you don’t reply twice to the same post Uses an AI prompt tuned for short, no-fluff, subreddit-friendly comments Softly mentions your brand only when it’s clearly relevant Posts the comment via Reddit’s API Saves post_id, comment_id, reply, permalink, status to Baserow Processes posts one-by-one with an optional short wait to be nice to Reddit ⚡ Requirements Reddit developer API Baserow account, table, and API token AI provider API (OpenAI / Anthropic / Gemini) ⚙️ Setup Instructions Create Baserow table Fields (user-field names exactly): post_id (unique), permalink, subreddit, title, created_utc, reply (long text), replied (boolean), created_on (datetime). Add credentials in n8n Reddit OAuth2* (scopes: read, submit, identity) and set a proper *User-Agent** string (Reddit requires it). LLM**: Google Gemini and/or Anthropic (both can be added; one can be fallback in the AI Agent). Baserow**: API token. Set the Schedule Trigger (Cron) Start hourly (or every 2–3h). Pacing is mainly enforced by the Wait nodes. Update “Check duplicate row” (HTTP Request) URL**: https://api.baserow.io/api/database/rows/table/{TABLE_ID}/?user_field_names=true&filter__post_id__equal={{$json.post_id}} Header**: Authorization: Token YOUR_BASEROW_TOKEN (Use your own Baserow domain if self-hosted.) Configure “Filter Replied Posts” Ensure it skips items where your Baserow record shows replied === true (so you don’t comment twice). Configure “Fetch Posts from Reddit” Set your keyword/search query (and time/sort). Keep User-Agent header present. Configure “Write Reddit Comment (AI)” Update your brand name** (and optional link). Edit the prompt/tone** to your voice; ensure it outputs a short reply field (≤80 words, helpful, non-salesy). Configure “Post Reddit Comment” (HTTP Request) Endpoint: POST https://oauth.reddit.com/api/comment Body: thing_id: "t3_{{$json.post_id}}", text: "{{$json.reply}}" Uses your Reddit OAuth credential and User-Agent header. Update user_agent value in header by your username n8n:reddit-autoreply:1.0 (by /u/{reddit-username}) Store Comment Data on Baserow (HTTP Request) POST https://api.baserow.io/api/database/rows/table/{TABLE_ID}/?user_field_names=true Header: Authorization: Token YOUR_BASEROW_TOKEN Map: post_id, permalink, subreddit, title, created_utc, reply, replied, created_on={{$now}}. Keep default pacing Leave Wait 5m (cool-off) and Wait 6h (global pace) → \~4 comments/day. Reduce waits gradually as account health allows. Test & enable Run once manually, verify a Baserow row and one test comment, then enable the schedule. 🤝 Need a hand? I’m happy to help you get this running smoothly—or tailor it to your brand. Reach out to me via email: imarunavadas@gmail.com

Screen and Score Investment Deals with AI using OpenAI, Gmail, and Telegram Automatically screens incoming deal submissions using AI, scores them against investment criteria, and routes to the right action. Who is this for? VC firms, PE funds, angel investors, or M&A advisors who receive deal flow via email or form submissions. What problem does this solve? Manually reviewing every pitch deck and deal memo is time-consuming. Most deals don't meet investment criteria. This agent screens, scores, and prioritizes deals so your team focuses on the best opportunities. How it works: New Email Received / Deal Submission Webhook - captures deals from email or form Normalize Email/Webhook Data - standardizes fields from either source Build Deal Text - combines email body + attachment info into screening text Has Deal Content? - validates there is enough content to screen Extract Deal Info - OpenAI - AI extracts company, industry, revenue, ask, team, highlights, red flags Score Deal - OpenAI - AI scores on 5 criteria (industry fit, revenue, growth, team, clarity) Is PASS? / Is REVIEW? - routes by verdict (PASS/REVIEW/REJECT) Telegram Alerts - notifies with deal summary and scores Log Deal to Pipeline Sheet - tracks all deals in a pipeline spreadsheet Setup: Add credentials: Gmail, OpenAI, Telegram Bot, Google Sheets Replace YOUR_TELEGRAM_CHAT_ID with your chat ID Create a Google Sheet with columns: received_at, company_name, industry, stage, revenue, ask_amount, overall_score, verdict, one_line_summary, recommendation, key_highlights, red_flags, sender_name, sender_email, source, industry_fit, revenue_stage, growth_trajectory, team_strength, deal_clarity Replace YOUR_GOOGLE_SHEET_ID with your sheet ID Customization: Edit the scoring criteria in the Score Deal OpenAI prompt Adjust score thresholds for PASS/REVIEW/REJECT Add Slack notifications instead of Telegram Add auto-decline email for REJECT deals Connect to a CRM instead of Google Sheets

Automatically qualify inbound demo requests, scrape prospect websites, and send AI-personalized outreach emails—all on autopilot. What This Workflow Does This end-to-end lead automation workflow helps SaaS companies qualify and nurture inbound leads with zero manual work until human approval. Key Features ✅ Smart Email Filtering - Automatically flags personal emails (Gmail, Yahoo, etc.) and routes them to a polite regret message ✅ Website Intelligence - Scrapes prospect websites and extracts business context ✅ AI Analysis - Uses OpenAI to score ICP fit, identify pain points, and find personalization opportunities ✅ Personalized Outreach - AI drafts custom emails referencing specific details from their website ✅ Human-in-the-Loop - Approval gate before sending to ensure quality control ✅ Professional Branding - Even rejected leads get a thoughtful response Perfect For B2B SaaS companies with inbound lead forms Sales teams drowning in demo requests Businesses wanting to personalize at scale Anyone needing intelligent lead qualification What You'll Need Jotform account (or any form tool with webhooks) Create your form for free on Jotform using this link OpenAI API key Gmail account (or any email service) n8n instance (cloud or self-hosted) Workflow Sections 📧 Lead Intake & Qualification - Capture form submissions and filter personal emails 🕷️ Website Scraping - Extract company information from their domain ❌ Regret Flow - Send polite rejection to unqualified leads 🤖 AI Analysis - Analyze prospects and draft personalized emails 📨 Approved Outreach - Human review + send welcome email Customization Tips: Update the AI prompt with your company's ICP and value proposition Modify the personal email provider list based on your market Adjust the regret email template to match your brand voice Add Slack notifications for high-value leads Connect your CRM to log all activities Time Saved: ~15-20 minutes per lead Lead Response: Under 5 minutes (vs hours/days manually)

Who is this for? This workflow is designed for business founders, CMOs, marketing teams, and landing page designers who want to automatically analyze their landing pages and get personalized, unconventional, high-impact conversion rate optimization (CRO) recommendations. It works by scraping the landing page content, then leveraging multiple AI models to roast the page and generate creative CRO ideas tailored specifically for that page. What this Workflow Does / Key Features Captures a landing page URL through a user-friendly form trigger. Scrapes the landing page HTML content using an HTTP request node. Sends the scraped content to a LangChain AI Agent, which orchestrates various AI models (OpenAI, Google Gemini, Mistral, etc.) for deep analysis. The AI Agent produces a friendly, fun, and unconventional “roast” of the landing page, explaining what’s wrong in human tone. Generates 10 detailed, personalized, easy-to-implement, and 2024-relevant CRO recommendations with a “wow” factor. Delivers the analysis and recommendations via Telegram message, Gmail email, and WhatsApp (via Rapiwa). Utilizes multiple AI tools and search APIs to enhance the quality and creativity of the output. Requirements OpenAI API credentials configured in n8n. Google Gemini (PaLM) API credentials for LangChain integration. Mistral Cloud API credentials for text extraction. Telegram bot credentials for sending messages. Gmail OAuth2 credentials for email delivery. Rapiwa API credentials for WhatsApp notifications. Running n8n instance with nodes: Form Trigger, HTTP Request, LangChain AI Agent, Telegram, Gmail, and custom Rapiwa node. How to Use — step-by-step Setup 1) Credentials Add your OpenAI API key under n8n credentials (OpenAi account 2). Add Google Gemini API key (Google Gemini (PaLM) Api account). Add Mistral Cloud API key (Mistral Cloud account). Set up Telegram Bot credentials (Telegram account). Set up Gmail OAuth2 credentials (Gmail account). Add Rapiwa API key for WhatsApp messages (Rapiwa). 2) Configure the Form Trigger Customize the form title, description, and landing page URL input placeholder if desired. 3) Customize Delivery Nodes Modify the Telegram, Gmail, and Rapiwa nodes with your desired recipient info and messaging preferences. 4) Run the Workflow Open the form URL webhook and submit the landing page URL to get a detailed AI-powered CRO roast and recommendations sent directly to your communication channels. Important Notes The AI Agent prompt is designed to create a fun and unconventional roast to engage users emotionally. Avoid generic advice. All CRO recommendations are personalized and contextual based on the scraped content of the provided landing page. Ensure all API credentials are kept secure and not hard-coded. Use n8n credentials management. Adjust the delivery nodes to match your preferred communication channels and recipients. The workflow supports expansion with additional AI models or messaging platforms as needed. 🙋 For Help & Community 👾 Discord: n8n channel 🌐 Website: devcodejourney.com 🔗 LinkedIn: Connect with Shakil 📱 WhatsApp Channel: Join Now 💬 Direct Chat: Message Now

Who 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 A Gmail trigger polls the inbox every minute for new unread emails and retrieves the current date. The full email message is fetched, and any existing processing labels are stripped from the thread. 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. 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. 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.

Monitor Indian (NSE/BSE) and US stock markets with intelligent price alerts, cooldown periods, and multi-channel notifications (Email + Telegram). Automatically tracks price movements and sends alerts when stocks cross predefined upper/lower limits. Perfect for day traders, investors, and portfolio managers who need instant notifications for price breakouts and breakdowns. How It Works Market Hours Trigger - Runs every 2 minutes during market hours Read Stock Watchlist - Fetches your stock list from Google Sheets Parse Watchlist Data - Processes stock symbols and alert parameters Fetch Live Stock Price - Gets real-time prices from Twelve Data API Smart Alert Logic - Intelligent price checking with cooldown periods Check Alert Conditions - Validates if alerts should be triggered Send Email Alert - Sends detailed email notifications Send Telegram Alert - Instant mobile notifications Update Alert History - Records alert timestamps in Google Sheets Alert Status Check - Monitors workflow success/failure Success/Error Notifications - Admin notifications for monitoring Key Features: Smart Cooldown**: Prevents alert spam Multi-Market**: Supports Indian & US stocks Dual Alerts**: Email + Telegram notifications Auto-Update**: Tracks last alert times Error Handling**: Built-in failure notifications Setup Requirements: 1. Google Sheets Setup: Create a Google Sheet with these columns (in exact order): A**: symbol (e.g., TCS, AAPL, RELIANCE.BSE) B**: upper_limit (e.g., 4000) C**: lower_limit (e.g., 3600) D**: direction (both/above/below) E**: cooldown_minutes (e.g., 15) F**: last_alert_price (auto-updated) G**: last_alert_time (auto-updated) 2. API Keys & IDs to Replace: YOUR_GOOGLE_SHEET_ID_HERE - Replace with your Google Sheet ID YOUR_TWELVE_DATA_API_KEY - Get free API key from twelvedata.com YOUR_TELEGRAM_CHAT_ID - Your Telegram chat ID (optional) your-email@gmail.com - Your sender email alert-recipient@gmail.com - Alert recipient email 3. Stock Symbol Format: US Stocks**: Use simple symbols like AAPL, TSLA, MSFT Indian Stocks**: Use .BSE or .NSE suffix like TCS.NSE, RELIANCE.BSE 4. Credentials Setup in n8n: Google Sheets**: Service Account credentials Email**: SMTP credentials Telegram**: Bot token (optional) Example Google Sheet Data: symbol upper_limit lower_limit direction cooldown_minutes TCS.NSE 4000 3600 both 15 AAPL 180 160 both 10 RELIANCE.BSE 2800 2600 above 20 Output Example: Alert: TCS crossed the upper limit. Current Price: ₹4100, Upper Limit: ₹4000.

Who’s it for Marketers, creators, and social managers who want hands-off reposting of a specific X (Twitter) user’s videos — with on-brand AI captions and clean, deduplicated logs. What it does / How it works On a schedule, the workflow resolves a target user, fetches recent tweets with media, filters to video posts, and writes them to Google Sheets for tracking and dedupe. It then builds a shareable video URL, generates a short caption via an AI model (OpenRouter), posts to your X account, and updates the sheet with completion status. Sticky notes inside the workflow explain each step, setup tasks, and best practices. How to set up Add credentials: Twitter (X) OAuth2, Google Sheets OAuth2, OpenRouter. Replace the demo Google Sheet with your own (document ID & sheet name). Set the target X username (or parameterize it). Adjust the schedule (interval/cron) and run a test execution. Verify logs and posting format, then enable. Requirements Twitter (X) OAuth2 credential Google Sheets OAuth2 credential OpenRouter credential (choose an affordable model) How to customize Edit the caption prompt (tone, hashtags count, CTAs, compliance lines). Add filters (language, min/max tweet age, exclude replies/retweets, since_id). Extend logging (timestamps, posted text, account, errors). Introduce a dry-run boolean to skip posting while testing. Swap the caption model or add retry rules for robustness. Security: Don’t hardcode tokens in HTTP nodes. Use n8n Credentials only and remove personal IDs before publishing.

Multichannel AI Assistant Demo for Chatwoot This simple n8n template demonstrates a Chatwoot integration that can: Receive new messages via a webhook. Retrieve conversation history. Process the message history into a format suitable for an LLM. Demonstrate an AI Assistant processing a user's query. Send the AI Assistant's response back to Chatwoot. Use Case: If you have multiple communication channels with your clients (e.g., Telegram, Instagram, WhatsApp, Facebook) integrated with Chatwoot, you can use this template as a starting point to build more sophisticated and tailored AI solutions that cover all channels at once. How it works A webhook receives the message created event from Chatwoot. The webhook data is then filtered to keep only the necessary information for a cleaner workflow. The workflow checks if the message is "incoming." This is crucial to prevent the assistant from replying to its own messages and creating endless loops. The conversation history is retrieved from Chatwoot via an API call using the HTTP Request node. This allows the assistant's interaction to be more natural and continuous without needing to store conversation history locally. A simple AI Assistant processes the conversation history and generates a response to the user based on its built-in knowledge base (see the prompt in the assistant node). The final HTTP Request node sends the AI-generated response back to the appropriate Chatwoot conversation. How to Use In Chatwoot, go to Settings → Integrations → Webhooks and add your n8n webhook URL. Be sure to select the message created event. In the HTTP Request nodes, replace the placeholder values: https://yourchatwooturl.com api_access_token You can find these values on your Chatwoot super admin page. The LLM node is configured to use OpenRouter. Add your OpenRouter credentials, or replace the node with your preferred LLM provider. Requirements An API key for OpenRouter or credentials for your preferred LLM provider. A Chatwoot account with at least one integrated channel and super admin access to obtain the api_access_token. Need Help Building Something More? Contact me on: Telegram:** @ninesfork LinkedIn:** George Zargaryan Happy Hacking! 🚀