Extract Structured Candidate Data from Resumes with GPT AI
Automates extraction of structured candidate data (name, email, skills, education) from resumes in PDF, DOC, TXT using OpenAI AI. Outputs to JSON or Google Sheets for HR/ATS integration.
This n8n workflow streamlines resume processing for recruiters and HR teams by automatically handling uploaded resume files in various formats like PDF, DOC, TXT, and CSV. It uses built-in n8n tools to extract raw text and leverages an OpenAI-powered LangChain agent to parse and structure key details including full name, email address, skill keywords, and education history.
The workflow eliminates manual data entry errors and saves hours of review time, enabling seamless integration into CRMs, ATS, or spreadsheets. Benefits include standardized candidate data for quick searching, filtering, and decision-making, with high accuracy from GPT's natural language understanding.
Ideal for hiring platforms, agencies, or internal HR automating high-volume resume screening. Customize by editing the AI prompt for additional fields like phone or LinkedIn, or swap outputs for webhooks to your ATS. Setup is simple: add OpenAI credentials, enable triggers, and optionally connect Google Sheets.
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How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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