ACORD forms are a standardized format for exchanging insurance data—but they’re complex, dense, and often vary slightly in layout across carriers. Manually extracting structured data from these forms is tedious, error-prone, and hard to scale. Tensorlake makes it easy to parse ACORD forms and extract consistent, schema-based outputs.
https://mintcdn.com/tensorlake-35e9e726/fVE8-oNRlpqs-U2A/images/colab_favicon_256px.png?fit=max&auto=format&n=fVE8-oNRlpqs-U2A&q=85&s=e7092abe8e3e91a0848a1509b42a50fb

Try it in a Colab Notebook

Try parsing a sample ACORD form with this Colab Notebook

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Why This Matters

Insurance companies rely on ACORD forms to:
  • Kick off underwriting
  • Manage policy changes
  • Process claims
But ACORD documents are often multi-page, cluttered with checkboxes, and hard for traditional OCR or LLMs to handle reliably.

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How Tensorlake Helps

Tensorlake uses layout-aware parsing and schema-driven extraction to:
  • Extract key fields like coverage type, carrier, policy number, and limits
  • Detect whether required signatures are present
  • Process multi-page forms into structured outputs you can use immediately
  • Integrate results into LangGraph or workflow tools to automate decisions