The Challenge
Teams spend 60% of their time on manual data extraction from contracts, invoices, and compliance documents. Existing OCR tools achieve under 70% accuracy on mixed-format inputs, and manual correction negates any automation benefits.
Our Approach
We build multi-stage AI pipelines combining traditional OCR with vision-language models. Documents are classified by type and quality, then routed to the optimal extraction path — achieving 90%+ accuracy with human review only for edge cases.
How We Deliver
Sample Analysis
Profile document types, layouts, and extraction targets from your real data
Pipeline Design
Route documents to optimal extraction strategies based on type and quality
Build
Implement classification, extraction, and validation flows
Calibrate
Tune accuracy with production samples, edge cases, and feedback loops
“What used to take a paralegal an entire day now completes in 40 minutes with higher accuracy.”
Tech Stack
Project Details
Prerequisites
- Document samples
- Output format requirements
- Integration endpoints
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