Hiring teams receive resumes in all shapes and formats. Parsing them into structured records unlocks automated routing, screening, and dashboarding. Tensorlake makes it easy to extract clean candidate data from PDFs and turn it into structured entries in Airtable, Notion, or an ATS.
Try parsing resumes using this notebook:

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Why This Matters

  • HR teams waste hours manually reviewing and copying resume data
  • Formats are inconsistent—many are scanned or contain tables and sections
  • LLM-based extraction is unreliable for structured fields like skills, schools, dates

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How Tensorlake Helps

  • Use schema-driven extraction to pull name, email, experience, skills, education
  • Handles layout quirks: columns, tables, and multi-page resumes
  • Detects strikethroughs or missing fields
  • Export results to CSV, Airtable, or direct integrations
Looking to auto-fill candidate profiles? Try it in the Playground or ask in Slack.