Pull Structured Data Out of Messy Documents
Paste an invoice, receipt, or contract excerpt — it's classified, labeled fields are pulled with confidence ratings, and line items broken out. Same pipeline we'd build into your finance, ops, or legal workflows.
Pick a sample or paste your own document, then hit Extract Fields to see structured data.
What you're seeing
The extracted JSON is validated against a strict schema before it leaves the server — no free-text hallucinations slip through. Confidence dots tell downstream systems which fields need a human eye.
Where this fits in production
AP automation, contract intake, expense classification, customs paperwork, KYC document review — anywhere a human currently re-types fields out of a PDF into a database. Plugs directly into Resend, S3, your ERP, or a queue.
What we'd build for you
Same engine, scaled: bring-your-own schema, batched OCR + LLM fallback, human-in-the-loop review queue, and metrics. Live in your stack within a Starter Sprint.
Model-agnostic — Claude, GPT, Gemini, or self-hosted. We pick what fits accuracy, cost, and data-residency requirements.