Layout-aware OCR and LLM extraction with validation rules and human-in-the-loop review — so most documents flow straight through, and exceptions reach the right person.
A complete document pipeline — intake, reading, extraction, validation and delivery — built for accuracy at volume.
Documents arrive by email, upload, scan, API or RPA — classified and routed automatically from the first page.
Layout-aware reading of text, tables, checkboxes and handwriting — the structure of the page is preserved, not flattened.
Fields, tables and key-values mapped to your schema — with a confidence score attached to every value.
Clauses and entities linked into a knowledge graph, enabling GraphRAG answers and obligation tracking across documents.
Validation rules and confidence thresholds route only the doubtful fields to a reviewer — nothing more.
Clean, validated data pushed into your ERP, CRM and data warehouse — with a full audit trail back to the source page.
OCR and LLM extraction with schema mapping and human-in-the-loop validation — from intake to structured data in your systems.
Documents arrive from every channel and are classified by type — invoice, claim, contract — before processing begins.
Layout-aware OCR reads text, tables and form fields while preserving the structure of the original document.
LLM extraction maps fields, tables and key-values to your schema, scoring its own confidence on every value.
Business rules check every record; low-confidence fields go to human review, and clean data lands in your systems.
From intake to structured, validated data delivered into your enterprise systems — with every field traceable to its source page.
A fixed-scope path from a sample document set to a measured straight-through rate.
We analyze your document types, volumes and target schema, and set an accuracy and straight-through target.
The pipeline processes your real documents — extraction accuracy measured field by field against the target.
Live with validation rules, a review queue and system delivery — operated by your team.
Full case study below — including how confidence thresholds decide which fields a human actually needs to see.
Manual keying of claim forms, invoices and reports was slow, costly and error-prone.
OCR and LLM-based extraction with schema mapping, plus a validation layer that flags low-confidence fields for human-in-the-loop review.
Most claims now flow straight through, with exceptions routed intelligently to reviewers.
Critical obligations, renewal dates and risks were buried across thousands of contracts.
Extracted clauses and entities into a knowledge graph, enabling GraphRAG Q&A, obligation tracking and cited, cross-contract answers.
Legal teams review faster, with full traceability back to source clauses.
Send us a sample of your document types — we'll return an extraction approach and straight-through estimate in days.
