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AI-Enriched Cold Outreach: Research → Draft → QA → Write-back ============================================================ What this template does ----------------------- Automates cold email drafting from a lead list by: 1. Enriching each lead with LinkedIn profile, LinkedIn company, and Crunchbase data 2. Generating a personalized subject + body with Gemini 3. Auto-reviewing with a Judge agent and writing back only APPROVED drafts to your Data Table Highlights ----------- Hands-off enrichment via RapidAPI; raw JSON stored back on each row Two-agent pattern: Creative Outreach Agent (draft) + Outreach Email Judge (QA) Structured outputs guaranteed by LangChain Structured Output Parsers Data Table–native: reads “unprocessed” rows, writes results to the same row Async polling with Wait nodes for scraper task results How it works (flow) ------------------- 1. Trigger: Manual (replace with Cron if needed) 2. Fetch leads: Data Table “Get row(s)” filters rows where email_subject is empty (pending) 3. Loop: Split in Batches iterates rows 4. Enrichment (runs in parallel): LinkedIn profile: HTTP (company_url) → Wait → Results → Data Table update → linkedin_profile_scrape LinkedIn company: HTTP (company_url) → Wait → Results → Data Table update → linkedin_company_scrape Crunchbase company: HTTP (url_search) → Wait → Results → Data Table update → crunchbase_company_scrape (All calls use host cold-outreach-enrichment-scraper with a RapidAPI key.) 5. Draft (Gemini): “Agent One” composes a concise, personalized email using row fields + enrichment + ABOUT ME block. Structured Output Parser enforces: ``json { "email_subject": "text", "email_content": "text" } ` 6. Prep for QA: “Email Context” maps email_subject, email_content, and email for the judge. 7. QA (Judge): “Judge Agent” returns APPROVED or REVISE (brief feedback allowed). 8. Route: If APPROVED → Data Table “Update row(s)” writes email_subject + email_body (a.k.a. email_content) back to the row. If REVISE → Skipped; loop continues. Required setup --------------- Data Table: “email_linkedin_list” (or your own) with at least: email, First_name, Last_name, Title, Location, Company_Name, Company_site, Linkedin_URL, company_linkedin (if used), Crunchbase_URL, email_subject, email_body, linkedin_profile_scrape, linkedin_company_scrape, crunchbase_company_scrape (string fields for JSON). Credentials: RapidAPI key for cold-outreach-enrichment-scraper (store securely as credential, not hardcoded) Google Gemini (PaLM) API configured in the Google Gemini Chat Model node ABOUT ME block: Replace the sample persona (James / CEO / Company Sample / AI Automations) with your own. Nodes used ----------- Data Table HTTP Request: AI Agent: Google Gemini Chat Model Split in Batches: Main Loop Set: RapidAPI-Key Customization ideas ------------------- Process flags: Add email_generated_at or processed` boolean to prevent reprocessing. Human-in-the-loop: Send drafts to Slack/Email for spot check before write-back. Delivery: After approval, optionally email the draft to the sender for review. Quotas & costs --------------- RapidAPI: Multiple calls per row (three tasks + result polls). Gemini: Token usage for generator + judge per row. Tune batch size and schedule accordingly. Privacy & compliance -------------------- You are scraping and storing person/company data. Ensure lawful basis, respect ToS, and minimize stored data.
by Johnny RafaelThis n8n template automates the collection, storage, and summarization of technology news and discussions from the n8n Community and Reddit (r/n8n). If you like staying informed but want to reduce daily manual browsing distractions, this workflow is perfect for you. How it works User Intent Detection: The workflow receives your Telegram message and uses an AI Agent (powered by Gemini/Groq) to intelligently classify your intent (Search, Deep-dive, or Casual Chat). Multi-Platform Scraping: Automatically fetches the latest discussions, topics, and comments from the official n8n Community and Reddit via HTTP Requests. Smart Summarization: Extracts complex HTML content and uses the AI to provide concise overviews, or deep-dives into specific forum threads with full contextual history. Seamless Delivery: Formats the AI's response into clean, chunked Telegram messages (handling limits smoothly) and delivers it straight to your chat. Daily Pulse: A scheduled trigger automatically aggregates the hottest topics every morning to keep you updated. How to use 1. Connect your Telegram Bot account to n8n. 2. Connect your Google Gemini and Groq API credentials. 3. (Optional) Connect your MongoDB instance if you want to enable long-term persistent chat memory. 4. Update the Chat ID in the Telegram nodes to route the scheduled Daily Pulse directly to your personal account or group. 5. Activate the workflow and start messaging your new AI assistant. Requirements n8n Version: Built and tested on n8n 2.9.4+. (Note: You may encounter errors on older versions. It is highly recommended to update to the latest n8n version to use this workflow effectively). Telegram Bot token. Google Gemini & Groq API keys. (Optional) MongoDB connection string. Customizing this workflow Change the AI Model: Swap the Gemini or Groq nodes for OpenAI, Claude, or any other supported LLM. Expand the Sources: Duplicate the HTTP Request nodes and adjust the HTML extractors to monitor other platforms like Discord or StackOverflow. Adjust the Schedule: Prefer chat over daily emails? Change the Cron expression to receive weekly summaries or disable it entirely to rely purely on on-demand Telegram queries. --- About the Author Created by: Nguyen Thieu Toan (Jay Nguyen) Email: me@nguyenthieutoan.com Website: nguyenthieutoan.com Company: CEO/Founder of GenStaff (genstaff.net) - AI Staffing Solutions Socials (Facebook / X / LinkedIn): @nguyenthieutoan More templates: n8n.io/creators/nguyenthieutoan
by Nguyễn Thiệu Toàn (Jay Nguyen)