Parse & evaluate HR candidates with GPT-4.1 and LinkedIn data in CSV/XLSX

AI-Powered HR Candidate Evaluation Agent with LinkedIn Data Enrichment in CSV/XLSX Format 🎯 Overview Transform your manual hiring process into an intelligent evaluation system that saves 15-20 minutes per candidate! This workflow automates the entire candidate assessment pipeline - from CSV/XLSX upload to AI-powered scoring with LinkedIn insights. When you upload a candidate list, this workflow automatically: - 📊 Converts your file into a formatted Google Sheet with RTL support - 🔍 Researches each candidate's recent LinkedIn posts via Apify - 🤖 Evaluates candidates using GPT-4.1 with context-aware scoring (0-100) - 💬 Generates professional Hebrew explanations for each score - 📈 Auto-sorts by score and applies professional formatting - ⚠️ Sends error alerts to keep everything running smoothly Cost per candidate: ~$0.05 | Time saved: 15-20 minutes each 👥 Who's it for? - HR teams drowning in candidate applications - Recruitment agencies needing consistent evaluation criteria - Hiring managers seeking data-driven candidate insights - Companies looking to scale their team - Anyone tired of manual spreadsheet juggling ⚡ How it works 1. Form submission triggers with CSV/XLSX upload 2. Google Drive stores the file and creates a new Sheet 3. Data extraction processes the file content 4. AI Agent loops through each candidate: - Fetches up to 3 recent LinkedIn posts via Apify - Analyzes qualifications against job requirements - Generates evaluation score and Hebrew explanation 5. Sheet formatting applies filters, sorting, and styling 6. Error handling notifies admin of any issues 🛠️ Setup Instructions Time to deploy: 15 minutes Requirements: - Google account (Drive + Sheets access) - OpenAI API key (GPT-4.1 access) - Apify API key (for LinkedIn scraping) - Gmail account (for error notifications) Step-by-step: 1. Import this template into your n8n instance 2. Configure Google credentials: - Connect Google Drive OAuth2 - Connect Google Sheets OAuth2 3. Add OpenAI API key to the GPT-4.1 node 4. Set up Apify credentials for LinkedIn scraping 5. Configure Gmail for error alerts (update email in "Send a message" node) 6. Update folder IDs in Google Drive nodes to your folders 7. Test with a sample CSV containing 2-3 candidates 8. Activate and share the form URL with your team! 📋 Input File Format Your CSV/XLSX should include these columns (Hebrew): - שם פרטי (First name) - שם משפחה (Last name) - חשבון לינקדאין (LinkedIn URL) - Your custom evaluation questions 🎨 Customization Options Easy tweaks: - Scoring criteria: Modify the AI agent's system message - Language: Switch from Hebrew to any language - Scoring rubric: Adjust the 50/25/15/10 weighting - LinkedIn posts: Change from 3 posts to more/fewer - Sheet styling: Customize colors and formatting Advanced modifications: - Add integration with your ATS (Greenhouse, Lever, etc.) - Connect to Slack for real-time notifications - Add multiple evaluation agents for different roles - Implement multi-language support - Add candidate email automation 💡 Pro Tips - Better LinkedIn data: Ensure candidates provide complete LinkedIn URLs (not just usernames) - Consistent scoring: Run batches of similar roles together for normalized scoring - Cost optimization: Adjust Apify settings to fetch only essential data - Scale smartly: Process in batches of min 10-20 for optimal performance ⚠️ Important Notes - LinkedIn scraping respects Apify's rate limits - Scores are relative within each batch - don't compare across different job roles - The workflow handles both CSV and XLSX formats automatically - Error notifications help you catch issues before they cascade 📊 Expected Results After implementation, expect: - Data-driven evaluation across candidates - Professional explanation for hiring decisions - Happy recruiters who can focus on human connection Built with ❤️ by Elay Guez