Intelligent Document Processing
Extract structured, validated JSON data from messy invoices, receipts, and PDF contracts.
Operational Problems Solved
Eliminate manual data entry. We engineer vision-language and OCR pipelines that ingest unstructured PDFs and output verified, schema-compliant database records.
System Architecture & Execution Flow
DETERMINISTIC PIPELINEUpload & OCR
Ingests PDF, normalizes orientation, and extracts visual layout tokens.
Schema Extraction
Extracts vendor, date, line items, subtotals, and tax into strict JSON.
Math Verification
Deterministic code verifies that sum(line items) == subtotal + tax.
Human Review
If mathematical discrepancy or low OCR confidence, prompts human reviewer.
ERP Ingestion
Exports verified payload directly into accounting or ERP database.
What We Deliver
Human-in-the-Loop Review Points
- Side-by-side visual reconciliation viewer showing PDF page alongside extracted fields
- 1-click correction updates the field and logs discrepancy for model tuning
Data Privacy & Security Boundaries
- Immediate secure file deletion from temporary processing storage after validation
- AES-256 encryption on all stored document archives
Technical Questions
How accurate is the document extraction on non-standard invoice formats?
Because we use layout-aware vision LLMs paired with deterministic mathematical reconciliation (checking that line items equal the stated subtotal), our pipeline achieves >98% accuracy on varied invoice layouts.
Scope a Production Pilot
We typically deliver a functional staging proof-of-concept for this capability within 2–3 weeks.
Recommended Tech Stack
Ready to scope your Intelligent Document Processing?
Share your current tech stack and dataset requirements. We will prepare an architecture proposal within one business day.
Zero obligation • Direct technical conversation with engineers • NDA upon request