Automated lead research – from LinkedIn to ready-to-send report
AI Prospect Researcher – Automated Lead Intelligence Workflow This workflow is built for professionals and teams who want to scale their B2B outreach with context-rich, personalized communication. It automates the full prospect research process — from pulling lead data and scraping LinkedIn profiles, to gathering real-time company insights and generating high-quality outreach reports with GPT-4. Using a combination of Apify, Perplexity AI, and OpenAI, this system creates a structured Google Doc for each lead, along with a logged summary in Google Sheets. Whether you’re preparing for sales calls, writing cold emails, or enriching your CRM — this tool delivers ready-to-use intelligence in minutes, without manual research. The process is modular, production-ready, and suitable for agencies, SDR teams, or founders managing outbound on their own. How it works Once triggered, the workflow takes in a list of leads from Google Sheets. For each lead, it uses Apify to scrape both the LinkedIn profile and company page (no login or cookies required). Then, Perplexity AI fetches contextual insights and competitor data. GPT-4 validates the research and synthesizes a structured summary of the individual and their company. Finally, a complete outreach report is generated and saved in Google Docs, while key data is logged in Sheets for tracking or follow-up automation. This is a powerful, production-grade automation for anyone serious about personalizing outreach without spending hours per lead.
By LukaszBValidate newsletter quality with GPT-5 quality gate before sending
Newsletter Quality Assurance with LLM Judge This sub-workflow validates newsletter quality before sending to customers. It's triggered by the main newsletter workflow and acts as an automated quality gate to catch data issues, broken layouts, or missing content. Who's it for E-commerce teams who want to automate newsletter quality checks and prevent broken or incomplete emails from reaching customers. Perfect for ensuring consistent brand quality without manual review. How it works Receives newsletter HTML - Triggered by parent workflow with the generated newsletter content Sends to test inbox - Delivers newsletter to LLM Judge's Gmail inbox to validate actual rendering Retrieves rendered email - Fetches the email back from Gmail to analyze how it actually renders (catches Gmail-specific issues) AI-powered validation - GPT-5 analyzes the newsletter against quality criteria: Verifies all 6 product cards have images, prices, and descriptions Checks layout integrity and date range formatting Detects broken images or unprocessed template variables Validates sale prices are lower than original prices Decision gate - Based on Judge's verdict: PASS: Returns approval to parent workflow → sends to customers BLOCK: Alerts admin via email → requires human review Set up steps Setup time: ~5 minutes Connect your Gmail account for sending test emails Update the Judge's email address in "Send newsletter to LLM Judge" node Update the admin alert email in error handling nodes Connect your OpenAI API credentials (GPT-5 recommended for heavy HTML processing) (Optional) Adjust quality thresholds in the Judge's system prompt Requirements Gmail account for test sends and retrieving rendered emails OpenAI API key (GPT-5 recommended) Parent workflow that passes newsletter HTML content How to customize Adjust validation strictness: Modify the Judge's system prompt to change what triggers BLOCK vs PASS Change product count: Update prompt if your newsletters have different numbers of products Add custom checks: Extend the system prompt with brand-specific validation rules Modify alert recipients: Update email addresses in error handling nodes 💡 Pro tip: The workflow validates the actual Gmail-rendered version to catch image loading issues and ensure consistent customer experience.
By Emir Belkahia