AI Solutions
Document Extraction
Pulling structured fields out of invoices, forms, and scanned records automatically, instead of someone re-typing them into a system by hand.
OCR · Structured Extraction · Document Intelligence
What it is
Most back-office work still starts with a human reading a document and typing what it says into another system. Document extraction replaces that step for high-volume, well-defined documents — invoices, applications, claims forms, ID documents — while keeping a human review path for anything the model is unsure about.
How it works
- 01Sample the real documents
Extraction accuracy is decided by document variety, not model choice — we start from your actual document set, not a clean demo sample.
- 02Define the fields and confidence bar
Which fields matter, what format each needs to land in downstream, and what confidence threshold triggers human review instead of auto-accept.
- 03Integrate into the real pipeline
Output goes where the data already needs to go — your ERP, CRM, or accounting system — not a separate dashboard nobody checks.
- 04Monitor accuracy in production
Extraction quality is tracked against real throughput, and drift (a new document layout, a new vendor format) gets caught, not discovered three months later.
Benefits
- Hours of manual data entry removed per week, not per demo
- A defined confidence threshold, so uncertain extractions are flagged, not silently guessed
- Output lands directly in the system it needs to reach, not a review-only sandbox
Frequently asked
What document types can this handle?
Anything with a repeatable structure — invoices, purchase orders, application forms, ID documents, scanned contracts. Free-form documents with no consistent structure are a worse fit and usually need a different approach.
What happens with a document the model can't read confidently?
It's flagged for human review rather than auto-accepted — the threshold for that is agreed with you up front, not buried in a default.
Does this replace our existing OCR tool?
Sometimes it augments it, sometimes it replaces it — depends on what you're already running. We evaluate against your current setup during scoping rather than assuming a rip-and-replace.
Also under AI Solutions
Routing tickets, applications, or claims to the right queue automatically.
Agentic WorkflowsA defined sequence of actions an LLM can carry out on its own, within stated limits.
Knowledge Retrieval (RAG)Answering questions from your own documents, with every answer traceable to a source.
Not sure this is the right fit yet?
A scope call is a lower-commitment way to find out before anything gets built.