Workflow Templates

WhatsApp AI Sales Agent using PDF Vector Store This workflow turns your WhatsApp number into an intelligent AI-powered Sales Agent that answers product queries using real data extracted from a PDF brochure. It loads a product brochure via HTTP Request, converts it into embeddings using OpenAI, stores them in an in-memory vector store and allows the AI Agent to provide factual answers to users via WhatsApp. Non-text messages are filtered and only text queries are processed. This makes the workflow ideal for building a lightweight chatbot that understands your product documentation deeply. Quick Start: 5-Step Fast Implementation Insert your WhatsApp credentials in the WhatsApp Trigger and WhatsApp Send nodes. Add your OpenAI API Key to all OpenAI-powered nodes. Replace the PDF URL in the HTTP Request node with your own brochure. Run the Manual Trigger once to build the vector store. Activate the workflow and start chatting from WhatsApp. What It Does This workflow converts a product brochure (PDF) into a searchable knowledgebase using LangChain vector embeddings. Incoming WhatsApp messages are processed and if the message is text, the AI Sales Agent uses OpenAI + the vector store to produce accurate, brochure-based answers. The AI responds naturally to customer queries, supports conversation memory across the session and retrieves information directly from the brochure when needed. Non-text messages are filtered out to maintain clean conversational flow. The workflow is fully modular: you can replace the PDF, modify AI prompts, plug into CRM systems or extend it into a broader sales automation pipeline. Who’s It For This workflow is ideal for: Businesses wanting a WhatsApp-based AI customer assistant. Sales teams needing automated product query handling. Companies with large product catalog PDFs. Marketers wanting a zero-code product brochure chatbot. Technical teams experimenting with LangChain + OpenAI inside n8n. Requirements to Use This Workflow To run this workflow successfully, you need: An n8n instance (cloud or self-hosted). A WhatsApp Business API connection. An OpenAI API key. A publicly accessible PDF brochure URL. Basic familiarity with n8n node configuration. Optional: A custom vector store backend (Qdrant, Pinecone) – the template uses in-memory storage. How It Works & How To Set Up 1. Import the Workflow JSON Upload the workflow JSON provided. 2. Configure WhatsApp Trigger Open WhatsApp Trigger Add your WhatsApp credentials Set the webhook correctly to match your n8n endpoint 3. Configure WhatsApp Response Nodes The workflow uses two WhatsApp send nodes: Reply To User** → Sends AI response Reply To User1** → Sends “unsupported message” reply Add your WhatsApp credentials to both. 4. Replace the PDF Brochure In get Product Brochure (HTTP Request): Update the url parameter with your own PDF 5. Run the PDF → Vector Store Setup (One-Time Only) Use the Manual Trigger ("When clicking ‘Test workflow’") to: Download the PDF Extract text Split into chunks Generate embeddings Store them in Product Catalogue vector store > You must run this once after importing the workflow. 6. Set OpenAI Credentials Add your OpenAI API Key to the following nodes: OpenAI Chat Model OpenAI Chat Model1 Embeddings OpenAI Embeddings OpenAI1 7. Review the AI Agent Prompt Inside AI Sales Agent, you can edit the system message to match: Your brand Your product types Your tone of voice 8. Activate the Workflow Once activated, WhatsApp users can chat with your AI Sales Agent. How to Customize Nodes? Here are common customization options: Customize the PDF / Knowledgebase Change the URL in get Product Brochure or Upload your own file via other nodes. Customize AI Behavior Edit the systemMessage inside AI Sales Agent: Change personality Set product rules Restrict/expand scope Change Supported Message Types Modify Handle Message Types switch logic to allow: Image → OCR Audio → Whisper Documents → Additional processing Modify WhatsApp Message Templates Inside the textBody of response nodes. Extend or replace Vector Store Swap vectorStoreInMemory with: Qdrant Pinecone Redis vector store By updating the vector store node. Add-Ons (Optional Enhancements) You can extend this workflow with: 1. Multi-language support Add OpenAI translation nodes before agent input. 2. CRM Integration Send user queries and chat logs into: HubSpot Salesforce Zoho CRM 3. Product Recommendation Engine Use embeddings similarity to suggest products. 4. Order Placement Workflow Connect to Stripe or Shopify APIs. 5. Analytics Dashboard Log chats into Airtable / Postgres for analysis. Use Case Examples Here are some practical uses: Product Inquiry Chatbot Customers ask about specs, pricing, or compatibility. Digital Catalog Assistant Converts PDF brochures into interactive WhatsApp search. Sales Support Bot Reduces load on human sales reps by handling common questions. Internal Knowledge Bot Teams access manuals, training documents, or service guides. Event/Product Launch Assistant Provides instant details about newly launched items. And many more similar use cases where an AI-powered WhatsApp assistant is valuable. Troubleshooting Guide | Issue | Possible Cause | Solution | | ------------------------------------------ | -------------------------------------- | ------------------------------------------------------------- | | WhatsApp messages not triggering workflow | Wrong webhook URL or inactive workflow | Ensure webhook is correct & activate workflow | | AI replies are empty | Missing OpenAI credentials | Add OpenAI API key to all AI nodes | | Vector store not populated | Manual trigger not executed | Run the Test Workflow trigger once | | PDF extraction returns blank text | PDF is image-based | Use OCR before text splitting | | “Unsupported message type” always triggers | Message type filter misconfigured | Check conditions in Handle Message Types | | AI not using brochure data | VectorStore tool not linked properly | Check connections between Embeddings → VectorStore → AI Agent | Need Help with Support & Extensions? If you need help setting up, customizing or extending this workflow, feel free to reach out to our n8n automation developers at WeblineIndia. We can help with Custom WhatsApp automation workflows AI-powered product catalog systems Integrating CRM, ERP or eCommerce platforms Building advanced LangChain-powered n8n automations Deploying scalable vector stores (Qdrant/Pinecone) And so much more.

📜 AI-Powered Contract Management Pipeline (Google Drive + VLM Run + Sheets + Calendar + Slack) ⚙️ What This Workflow Does This workflow automatically extracts, organizes, and tracks legal contract details from documents uploaded to Google Drive. Using VLM Run’s Execute Agent, it parses key metadata such as contract ID, parties, dates, and terms — then stores, alerts, and schedules reminders through Google Sheets, Calendar, and Slack. 🧩 Requirements Google Drive OAuth2** for monitoring and downloads VLM Run API credentials** with Execute Agent access Google Sheets OAuth2** for structured record storage Google Calendar OAuth2** for key date reminders Slack API credentials** for team notifications A reachable Webhook URL (for receiving parsed contract data) ⚡Quick Setup Configure Google Drive OAuth2 and create upload folder and folder for saving extracted images. Install the verified VLM Run node by searching for VLM Run in the node list, then click Install. Once installed, you can start using it in your workflows. Add VLM Run API credentials for document parsing. Configure Google Sheet and Calendar. For Google Sheet, from the document list, pick your Google Sheet (e.g., test). Then select the sheet inside it (e.g., Sheet1). Set the operation to Append Row — this will add new contract details as new rows. Turn on Map Each Column Manually. Match each contract field (like Contract ID, Title, Parties, Effective Date, Termination Date) to its corresponding column in your Google Sheet. Configure Slack for notifications. ⚙️ How It Works Monitor Contract Uploads – Watches a target Google Drive folder for new file uploads (PDFs, images, or scans). Download Contract File – Automatically downloads new contracts for AI analysis. VLM Run ContractParser – Sends the file to the VLM Run Execute Agent, which extracts structured contract data, including: Contract ID Title Parties (with roles) Property address Effective date Termination date Rent, deposit, payment terms, and governing law Receive Contract Data – The webhook endpoint receives the structured JSON response. Format Contract Data – Normalizes fields, formats dates, and prepares for storage. Save to Expense Database (Google Sheets) – Appends extracted data to a master Google Sheet for centralized contract tracking. Notify via Slack – Posts a concise summary to a Slack channel, showing key contract details for visibility. Create Calendar Events – Automatically schedules Google Calendar events for: Effective Date Termination Date Renewal Reminder (60 days before termination) 💡 Why Use This Workflow Manual contract management is error-prone and time-consuming key details like renewal dates, payment terms, or termination clauses often get lost in email threads or folders. This workflow ensures: Zero missed deadlines** automatic Google Calendar reminders keep your team on track. Instant team visibility** - Slack notifications keep legal, finance, and operations aligned. End-to-end automation** no need for manual parsing, data entry, or follow-ups. 🧠 Perfect For Legal teams automating contract intake and tracking Real estate or lease management workflows Finance or procurement teams needing expiration alerts Organizations centralizing contract metadata in Sheets 🛠️ How to Customize Modify Extraction Fields Edit the VLM Run Execute Agent schema to add fields like contract value, payment schedule, department, or contact email. Change Storage Swap Google Sheets for Airtable, Notion, or BigQuery if you manage large datasets or need relational tracking. Customize Notifications Send Slack alerts only for high-value or expiring contracts, and tag relevant teams (e.g., @legal, @finance). Add Calendar Events Auto-create events for reviews or payment milestones using extra date fields. Add Approvals or Signatures Insert a Google Form or Slack approval step, or trigger DocuSign for e-signature automation. ⚠️ Community Node Disclaimer This workflow uses community nodes (VLM Run) that may need additional permissions and custom setup.

**Get Started ** Creator: @obisdev This workflow powers a fully automated WhatsApp chatbot using a self-hosted Venom Bot instead of the official WhatsApp Business API. It integrates Google Gemini AI to generate intelligent, conversational responses and optionally pulls factual information from a Google Docs-based knowledge base. Designed for small businesses and creators, the bot can maintain contextual memory across messages and act as a smart virtual assistant for sales, support, and lead generation. Overview This n8n workflow connects with a custom-hosted Venom Bot that simulates WhatsApp Web to send and receive messages. It uses a Webhook trigger to receive incoming messages, processes them with an AI Agent powered by Gemini, optionally pulls extra data from a Google Doc or Google Sheet, and sends a smart reply back through the Venom Bot. The workflow also includes a memory system to retain user context, making it capable of handling follow-up questions and dynamic conversations. Who this workflow is for Small Business Owners: Offer 24/7 customer service on WhatsApp without paying for Meta’s Business API. Freelancers & Developers: Build, test, and monetize intelligent bots without the approval process of WhatsApp’s API. Online Sellers & Creators: Handle FAQs, orders, and customer inquiries via WhatsApp on autopilot. Marketers: Deploy campaign bots that respond to DMs with personalized product suggestions or lead captures. Hackers & Builders: Experiment with unofficial APIs to control WhatsApp reliably without breaking TOS for small-scale use. Tools Used n8n: The automation platform managing flow, context, and decision logic. Venom Bot: A Node.js-based, self-hosted WhatsApp Web bot used to send/receive messages. Google Gemini: AI engine for generating context-aware replies. Google Docs (Optional): Acts as a structured knowledge base for business info or FAQs. Google Sheets (Optional): Feeds real-time or structured data into your AI responses. How to Install Import the Workflow: Download the .json and import it into your n8n instance. Set Up Venom Bot: Deploy Venom Bot (on VPS or local) and set it to send messages to your Webhook URL. Webhook Configuration: Update the Webhook node in n8n and set 'Respond' to "Using Respond to Webhook Node". Connect Google Gemini: Add your Gemini API key in n8n credentials. Set Up Google Docs (Optional): Link the document containing your knowledge base. Enable Conversational Memory: Use ={{ $("Process Message").first().json.from }} as the session ID. Check API Key Matching: Ensure the API_SECRET_KEY in Venom .env matches the authorization header in n8n. Customize Persona & Prompts: Update the AI Agent system message to fit your brand tone. Use Cases Customer service without WhatsApp Business API Smart lead generation bots E-commerce order responders AI-powered chatbot for DMs FAQ responder with knowledge base support Connect with Me Email: obisdev@gmail.com Twitter/X: @obisdev GitHub: github.com/obisdev Visit: obisdev.vercel.app #n8n #whatsappautomation #venombot #chatbots #noapi #geminiapi #googleworkspace #aiassistant #nocode #vpsautomation #chatbotwithoutapi #automationtools #customerbot #salesautomation #googleintegration

How It Works The webhook receives incoming profiles and extracts relevant demographic, financial, and credential data. The workflow then queries the programs database to identify suitable options, while the AI generates personalized recommendations based on eligibility and preferences. A formal recommendation letter is created, followed by a drafted outreach email tailored to coordinators. Parsers extract structured data from the letters and emails, a Slack summary is prepared for internal visibility, and the final response is sent to the appropriate recipients. Setup Steps Configure AI agents by adding OpenAI credentials and setting prompts for the Program Matcher, Letter Writer, and Email Drafter. Connect the programs database (Airtable or PostgreSQL) and configure queries to retrieve matching program data. Set up the webhook by defining the trigger endpoint and payload structure for incoming profiles. Configure JSON parsers to extract relevant information from profiles, letters, and emails. Add the Slack webhook URL and define the summary format for generated communications. Prerequisites OpenAI API key Financial programs database Slack workspace with webhook User profile structure (income, GPA, demographics) Use Cases Universities automating 500+ annual applicant communications Scholarship foundations personalizing outreach at scale Customization Add multilingual support for international applicants Include PDF letter generation with signatures Benefits Reduces communication time from 30 to 2 minutes per applicant, ensures consistent professional quality

📊 Description Generate high-quality, SEO-optimized content briefs automatically using AI, real-time keyword research, SERP intelligence, and historical content context. This workflow standardizes user inputs, fetches search metrics, analyzes competitors, and produces structured SEO briefs with quality scoring and version control. It also stores all versions in Google Sheets and generates HTML previews for easy review and publishing. 🤖📄📈 What This Template Does Normalizes user input from the chat trigger into structured fields (intent, topic, parameters). ✏️ Fetches real-time keyword metrics such as search volume, CPC, and difficulty from DataForSEO. 🔍 Retrieves SERP insights through SerpAPI for top competitors, headings, and content gaps. 🌐 Loads historical brief versions from Google Sheets for continuity and versioning. 📚 Uses an advanced GPT-4o-mini agent to generate a complete SEO brief with title, metadata, keywords, outline, entities, and internal links. 🤖 Calculates detailed SEO, differentiation, and completeness quality scores. 📊 Validates briefs against quality thresholds (outline length, keywords, word count, overall score). ⚡ Stores approved briefs in Google Sheets with version control and timestamping. 🗂️ Generates an HTML preview with styled formatting for team review or CMS use. 🖥️ Sends Slack alerts when a brief does not meet quality standards. 🚨 Key Benefits ✅ Fully automated SEO content brief generation ✅ Uses real-time keyword + SERP + competitor intelligence ✅ Ensures quality through automated scoring and validation ✅ Built-in version control for content operations teams ✅ Beautiful HTML preview ready for editors or clients ✅ Reduces research time from hours to minutes ✅ Ideal for content agencies, SEO teams, and AI-powered workflows Features Chat-triggered brief generation Real-time DataForSEO keyword metrics SERP analysis tool integration GPT-4o-mini structured AI agent Google Sheets integration for storing & retrieving versions Automated quality scoring (SEO, gaps, completeness) HTML preview builder with rich formatting Slack alerting for low-quality briefs Semantic entities, content gaps, competitor insights Requirements OpenAI API (GPT-4o-mini or compatible model) DataForSEO access credentials (Basic Auth) SerpAPI key for SERP extraction Google Sheets OAuth2 integration Optional: Slack webhook for quality alerts Target Audience SEO teams generating large amounts of content briefs Content agencies scaling production with automation Marketing teams building data-driven content strategies SaaS teams wanting automated keyword-based briefs Anyone needing structured, high-quality content briefs from chat Step-by-Step Setup Instructions Connect your OpenAI API credential and confirm GPT-4o-mini availability. 🔌 Add DataForSEO HTTP Basic Auth for keyword metrics. 📊 Connect SerpAPI for SERP analysis tools. 🌐 Add Google Sheets OAuth2 and link your content_versions sheet. 📄 Optional: Add a Slack webhook URL for quality alerts. 🔔 Test by sending a topic via the chat trigger. Review the generated SEO brief and HTML preview. Enable the workflow for continued use in your content pipeline. 🚀

🚀 AI Marketing Campaign Generator Upload product image + details → Get complete professional marketing campaign with 5 custom-generated assets automatically. 🤖 AI Model GPT-4o Mini (OpenAI) - For campaign strategy | Prompt Image generation GPT Image-1 (OpenAI) - For visual asset generation 🔑 Required API Keys OpenAI API - AI analysis & image generation Google Drive API - Asset storage & organization 🎯 What It Generates 5 Marketing Assets: Instagram Post, Instagram Story, Website Banner, Ad Creative, Testimonial Graphic Brand Strategy: Colors, tone, positioning from your product image Campaign Strategy: Messaging, target audience, objectives Visual Analysis: Extracts colors, materials, styling from uploaded image ⚙️ Setup Import JSON to n8n Add OpenAI & Google Drive credentials Configure Google Drive folder for asset storage Deploy form webhook Test with product image upload 📱 How It Works Upload product image → AI analyzes visual + text → Generates complete campaign → Creates 5 custom marketing assets → Saves to Google Drive

Who is this for? This workflow is for healthcare professionals, consultants, coaches, and service businesses who want to completely automate their appointment booking system via WhatsApp — without manual intervention for reservations, availability checks, or cancellation management. What problem is this workflow solving? / Use case Managing appointments manually via WhatsApp is extremely time-consuming: checking availability, confirmations, rescheduling, cancellations. This workflow automates the entire process — from initial request to final confirmation — allowing your clients to book, modify, or cancel appointments 24/7, in natural language, directly via WhatsApp. What this workflow does Processes multi-modal messages (text, audio, images) from WhatsApp Business API Detects message type and routes to appropriate processing (Whisper for audio, GPT-4 Vision for images) Uses AI Agent with 5 Cal.com tools to manage complete appointment lifecycle Checks real-time availability in your Cal.com calendar Books appointments autonomously without human intervention Handles cancellations and rescheduling requests Maintains conversation context with Simple Memory for natural exchanges Formats responses with Unicode bold for better WhatsApp readability Sends automated replies directly to the client The result: a fully automated 24/7 appointment management system via WhatsApp. Setup 1. WhatsApp Business API Connect your WhatsApp Business API account in n8n. Set up the webhook in Facebook Developer Console (Webhook → Messages → Subscribe). Add your phone_number_id and access token credentials. 2. Cal.com Create a Cal.com account and configure your calendar. Generate an API Key from Cal.com settings. Set up your event types (duration, availability, pricing). Add your Cal.com API credentials in n8n. 3. OpenAI Get an OpenAI API key (for GPT-4, Whisper, and Vision). Add your OpenAI credentials in n8n. The workflow uses GPT-4 for conversation, Whisper for audio transcription, and GPT-4 Vision for image analysis. 4. Customize the AI Agent Edit the System Message to define your agent's personality, tone, and business context. Adjust timezone in tool parameters (default: Europe/Paris). Configure event type IDs for different appointment types. 5. Test & activate Test with different message types (text, audio, image) from WhatsApp. Verify appointments are created correctly in Cal.com. Switch to production mode and activate the workflow. This workflow helps you build a fully autonomous AI booking assistant, transforming WhatsApp into a 24/7 appointment management system. Need help customizing? Contact me for consulting and support: LinkedIn / Youtube

Automate GitHub pull request reviews and labeling using OpenAI This workflow automates the first line of code review for your development team. By leveraging OpenAI, it analyzes pull request diffs, assigns descriptive labels based on change size and category, posts summary comments back to GitHub, and keeps your team informed via Slack. Who’s it for? DevOps Engineers** looking to standardize PR triage. Team Leads** who want to provide instant feedback to developers. Open Source Maintainers** managing high volumes of contributions. Development Teams** aiming to reduce manual overhead in code reviews. How it works / What it does Trigger: The workflow starts via a GitHub PR Webhook when a pull request is opened or synchronized. Data Gathering: It extracts PR metadata and uses the GitHub Node and HTTP Request Node to fetch a list of changed files and the raw code diff. Analysis: A Code Node categorizes the changes (e.g., size labels like size/S or size/L). AI Review: The AI Agent (powered by OpenAI) analyzes the code diff to generate a quality score, summary, and specific strengths/concerns. Action: The GitHub Node updates the PR with relevant labels. An automated review comment is posted to the PR discussion. A summary is sent to a Slack channel. Reporting: All review data is logged into Google Sheets for long-term tracking and analytics. Requirements GitHub Account:** OAuth credentials with repository access. OpenAI API Key:** For the Chat Model (recommends GPT-4o-mini or higher). Slack Workspace:** A bot token to post to the #code-reviews channel. Google Sheets:** A spreadsheet with headers matching the PR metadata. How to set up GitHub Webhook: Configure your GitHub repository to send "Pull request" events to the Webhook URL provided by this workflow. Credentials: Authenticate your GitHub, OpenAI, Slack, and Google Sheets accounts in their respective nodes. Google Sheets: Select your target Spreadsheet and Sheet name in the "Log to Sheets" node. Slack: Ensure the Slack bot is invited to the channel specified in the "Notify Slack" node. How to customize AI Prompt:* Modify the "System Message" in the *AI Code Reviewer** node to reflect your team's specific coding standards or preferred review tone. Labeling Logic:** Edit the "Analyze File Changes" node to add custom labels based on file paths (e.g., frontend, documentation). Review Logic:* Add an *If Node** after the AI analysis to only auto-approve PRs with a quality score higher than 90.

What Problem Does It Solve? Customers often ask product questions or prices in comments. Businesses waste time replying manually, leading to delays. Some comments only need a short thank-you reply, while others need a detailed private response. This workflow solves these by: Replying with a friendly public comment. Sending a private message with details when needed. Handling compliments, complaints, and unclear comments in a consistent way. How to Configure It Facebook Setup Connect your Facebook Page credentials in n8n. Add the webhook URL from this workflow to your Facebook App/Webhook settings. AI Setup Add your Google Gemini API key (or swap for OpenAI/Claude). The included prompt is generic — you can edit it to match your brand tone. Optional Logging If you want to track processed messages, connect a Notion database or another CRM. How It Works Webhook catches new Facebook comments. AI Agent analyzes the comment and categorizes it (question, compliment, complaint, unclear, spam). Replying: For questions/requests → public reply + private message with full details. For compliments → short thank-you reply. For complaints → apology reply + private message for clarification. For unclear comments → ask politely if they need help. For spam/offensive → ignored (no reply). Replies and messages are sent instantly via the Facebook Graph API. Customization Ideas Change the AI prompt to match your brand voice. Add forwarding to Slack/Email if a human should review certain replies. Log conversations in Notion, Google Sheets, or a CRM for reporting. Expand to Instagram or WhatsApp with small adjustments. If you need any help Get In Touch

How it Works This workflow lets you build a Messenger AI Agent capable of understanding text, images, and voice notes, and replying intelligently in real time. It starts by receiving messages from a Facebook Page via a Webhook, detects the message type (text, image, or audio), and routes it through the right branch. Each input is then prepared as a prompt and sent to an AI Agent that can respond using text generation, perform quick calculations, or fetch information from Wikipedia. Finally, the answer is formatted and sent back to Messenger via the Graph API, creating a smooth, fully automated chat experience. Set Up Steps Connect credentials Add your OpenAI API key and Facebook Page Access Token in n8n credentials. Plug the webhook Copy the Messenger webhook URL from your workflow and paste it into your Facebook Page Developer settings (Webhook → Messages → Subscribe). Customize the agent Edit the System Message of the AI Agent to define tone, temperature, and purpose (e.g. “customer support”, “math assistant”). Enable memory & tools Turn on Simple Memory to keep conversation context and activate tools like Calculator or Wikipedia. Test & deploy Switch to production mode, test text, image, and voice messages directly from Messenger. Benefits 💬 Multi-modal Understanding — Handles text, images, and audio messages seamlessly. ⚙️ Full Automation — End-to-end workflow from Messenger to AI and back. 🧠 Smart Replies — Uses OpenAI + Wikipedia + Calculator for context-aware answers. 🚀 No-Code Setup — Build your first Messenger AI in less than 30 minutes. 🔗 Extensible — Easily connect more tools or APIs like Airtable, Google Sheets, or Notion.

This workflow deploys a fully customizable AI chatbot that can be embedded on any website, from custom-coded sites to platforms like WordPress. The chatbot is powered by n8n, uses Supabase for memory and RAG, and integrates SerpAPI, Google Calendar, SMTP, and Google Sheets to automate responses, collect leads, and follow up intelligently. Unlike typical widgets, this bot captures name and email before chatting, enabling personalized, human-like conversations and smart lead tracking. Check demo here 🎯 Core Features 💡 Universal Embedding – Works on any site (custom HTML or WordPress) using a single embed snippet. 🧠 AI Agent Node + RAG – Powered by Gemini (or any AI model) with Supabase as memory for contextual replies. 🌐 SerpAPI Integration – Lets the agent search the internet for real-time information. 📅 Google Calendar & Sheets – Logs leads, appointments, and chat summaries. 📧 SMTP Node – Sends personalized follow-up emails directly to new leads. 🪪 Lead Capture – Requires users to enter their name and email before chatting, creating personalized sessions. ⚙️ How It Works Chat Trigger: The widget sends user input to your n8n webhook set to production mode. AI Processing: The AI Agent node handles the response logic with memory and RAG context from Supabase. Integrations: SerpAPI → Real-time search. Google Calendar & Sheets → Stores lead data and events. SMTP Node → Sends automatic thank-you or follow-up emails. Response: The chatbot replies instantly on your website, maintaining session memory. 🧩 Quick Setup Steps Fork or use the Open Source Repo: The widget script is hosted via CDN from your GitHub repo and is fully editable. Embed the Widget: Copy and paste the following snippet into your site’s <head> or footer (or use a plugin like Insert Headers and Footers on WordPress): <link href="https://cdn.jsdelivr.net/npm/@n8n/chat/dist/style.css" rel="stylesheet" /> <script> window.ChatWidgetConfig = { webhook: { url: '', // production webhook URL route: 'general' }, branding: { logo: '', // your logo URL name: 'CustomCX Agent', welcomeText: 'Hi 👋, how can we help?', responseTimeText: 'We typically respond right away', }, style: { primaryColor: '#854fff', secondaryColor: '#6b3fd4', position: 'right', backgroundColor: '#ffffff', fontColor: '#333333', } }; </script> <script src="https://cdn.jsdelivr.net/gh/shadrack-ago/n8n/widget.js?v=2.6"></script> Connect Integrations: Add your Supabase, SerpAPI, Google, and SMTP credentials in n8n. Update your webhook URL in the script above. Deploy: Activate the workflow, refresh your site, and start chatting with your AI assistant. 🚀 Why Use This Template Works with any website or CMS. Captures and stores qualified leads automatically. Open source — easily modify, brand, or extend it. Seamlessly integrates AI, CRM, and communication tools.

Social Media Intelligence Workflow with Bright Data and OpenAI Get a 360 Social media presence report for a person Who's it for Business development professionals, recruiters, sales teams, and market researchers who need comprehensive social media intelligence on individuals for lead qualification, due diligence, partnership evaluation, or candidate assessment. How it works Enter target person's details through the web form (name, company, location) AI Discovery Agent searches across selected platforms using name variations Profile validator verifies discovered profiles with confidence scoring Platform-specific agents analyze each profile using Bright Data MCP tools GPT-4 synthesizes all data into a comprehensive intelligence report Report automatically generated as formatted Google Doc with direct link Requirements Bright Data MCP account with PRO access (Get your Bright Data API key here) OpenAI API key (or alternative LLM provider) Google Drive OAuth connection for report delivery n8n self-hosted instance or cloud account How to set up Update Bright Data credentials: Find "Bright Data MCP" node (look for red warning note) Replace YOUR_BRIGHT_DATA_TOKEN_HERE with your actual token Update UNLOCKER_CODE_HERE with your unlocker code Update Google Drive settings: Find "Create Empty Google Doc" node Select target folder there Configure your LLM credentials (OpenAI or alternative) Test with your own name using "Basic" search depth Watch Youtube Tutorial How to customize the workflow Add platforms**: Extend the Switch node with new cases and create corresponding prompt builders Modify analysis depth**: Edit the platform-specific prompt builders to focus on different metrics Change report format**: Update the final LLM Chain prompt to adjust report structure Add notifications**: Insert Slack or email nodes after report generation Adjust confidence thresholds**: Modify validators to change profile verification requirements Alternative outputs**: Replace Google Docs with PDF, Excel, or webhook to CRM