AI & Automation

Document AI Services

Document AI automatically reads unstructured documents — invoices, contracts, claims forms, ID proofs — and extracts the specific fields you need into structured data, combining OCR with LLM-based understanding so it handles layout variation that breaks traditional template-based extraction.

Documents don't come in one format

Traditional OCR templates break the moment a vendor changes their invoice layout. Manual data entry is accurate but doesn't scale and is expensive at volume. Modern document AI combines OCR (to read the text and layout) with an LLM (to understand context and extract the right fields regardless of exact format), so it handles the variation that breaks rule-based systems.

Invoices & receipts

Extract vendor, line items, amounts, and tax details regardless of the invoice's layout or format.

Contracts & agreements

Pull key clauses, dates, parties and obligations for review or downstream processing.

Forms & ID documents

Extract structured fields from KYC documents, claims forms and applications for automated processing.

How we build a document AI pipeline

1

Sample document review

Review a real sample set of your documents to understand format variation and the exact fields you need extracted.

2

Extraction pipeline build

Combine OCR with LLM-based extraction against your defined schema, with confidence scoring per field.

3

Validation rules

Add business-logic checks (totals matching line items, date ranges, required fields) to catch extraction errors automatically.

4

Human-in-the-loop review

Route low-confidence extractions to a review queue instead of silently accepting uncertain data.

Where document AI is used

Accounts payable automation

Auto-extract and validate invoice data before it hits your accounting system, cutting manual entry to near zero.

EnterpriseManufacturing

Contract analysis

Extract key terms and obligations across a large contract portfolio for review or compliance tracking.

LegalBFSI

KYC & claims processing

Extract and validate data from ID documents and claims forms to speed up onboarding and claims turnaround.

NBFCInsurance

Tools we build document AI with

GPT-4o Vision Tesseract / Cloud OCR LayoutLM Python FastAPI PostgreSQL

Why teams automate document processing

Handles format variation that breaks template-based OCR, without a rule update every time a vendor changes layout.

Confidence scoring means uncertain extractions get reviewed, not silently accepted as fact.

Cuts manual data-entry hours dramatically at high document volumes.

Structured output plugs directly into your existing accounting, CRM or claims system.

Document AI we've shipped

Frequently asked questions

What is document AI?
Document AI automatically extracts structured data from unstructured documents like invoices, contracts and forms, combining OCR to read the text/layout with an LLM to understand context and extract the right fields regardless of exact format.
How is this different from regular OCR?
Traditional OCR just converts an image to text and often relies on fixed templates. Document AI adds LLM-based understanding on top, so it can correctly extract fields even when the document layout varies between vendors or versions.
How accurate is the extraction?
Accuracy depends on document quality and complexity; every extracted field gets a confidence score, and low-confidence extractions are routed to human review rather than accepted automatically.
Can it handle handwritten documents?
Handwriting recognition is possible but generally less reliable than printed text — we assess this during the sample document review before committing to an approach.
What document formats can it process?
PDFs, scanned images, and photos of physical documents are all supported; quality of the source scan affects accuracy.
How long does document AI take to set up?
A focused pipeline for one document type typically takes a few weeks, including sample review, extraction schema design, and validation-rule setup.

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