Parse & Evaluate HR Candidates with GPT-4.1 and LinkedIn Data in CSV/XLSX

Description

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

Form submission triggers with CSV/XLSX upload
Google Drive stores the file and creates a new Sheet
Data extraction processes the file content
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
Sheet formatting applies filters, sorting, and styling
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:
Import this template into your n8n instance
Configure Google credentials:
Connect Google Drive OAuth2
Connect Google Sheets OAuth2
Add OpenAI API key to the GPT-4.1 node
Set up Apify credentials for LinkedIn scraping
Configure Gmail for error alerts (update email in "Send a message" node)
Update folder IDs in Google Drive nodes to your folders
Test with a sample CSV containing 2-3 candidates
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