Invoices and purchase orders
Line-item extraction that survives every supplier's layout.
Document Intelligence
Extract insight from
any document.
Turn PDFs, contracts, invoices, and scanned files into structured data and actionable intelligence — powered by LLMs and purpose-built extraction pipelines.
What we deliver
- PDF, Word, image, and scanned document processing
- Structured data extraction with LLM + OCR
- Contract review and clause identification
- Invoice and receipt parsing pipelines
- Semantic search across large document libraries
- Audit trail and human review workflows
Documents teams stop processing by hand
Contracts
Clause identification, obligations and dates lifted into a reviewable summary.
Claims and applications
Intake packets validated and routed with the missing pieces flagged.
Identity and KYC documents
Structured capture with confidence thresholds and a review queue.
FAQ
Frequently asked questions
- How accurate is AI document extraction?
- Accuracy only means something against a specific test set of your documents, which is why we build one first. The practical target is not perfection but a confidence threshold above which extraction is automatic and below which a human reviews it.
- Is this just OCR?
- OCR reads characters. Document intelligence understands structure and meaning — which number is the total, which date is the due date, which clause is the termination clause — and returns fields your systems can use.
- What about handwriting and poor scans?
- Both are handled with reduced confidence, which is exactly what the review queue is for. We measure it on your real documents rather than promising a number up front.
- Where is our document data processed and stored?
- A decision we make with you, including region and retention. If Indian personal data is involved, see our note on the DPDP Act for what erasure and retention obligations mean in practice.
- How long before it is usable?
- A narrow first version on one document type is typically weeks. Gathering and labelling a representative sample is usually the pacing item, not the model.