AI document processing systems that extract, classify, and route documents automatically built on the same case-management engineering behind Appeals Doctor.
Documents are unstructured until someone reads them
Every document your team reads by hand to pull out a date, an amount, a classification, or a next step is a place where volume outpaces headcount. Teams that scale past this build a pipeline that extracts the structure automatically and routes documents into the right workflow the ones that don't stay bottlenecked by however many people can read.
What we build
- Field extraction from structured and unstructured documents, including scans
- Document classification and automatic routing into the right workflow
- Validation logic that flags low-confidence extractions for human review instead of guessing
- Integration with your existing case management or workflow tools
- Audit trails showing what was extracted, how, and with what confidence
How we work
Start from real documents your team processes today, not a clean sample set
Build extraction with confidence scoring, so uncertain cases route to a human
Wire the output into your existing workflow tool rather than a new dashboard nobody opens
Monitor accuracy against human-reviewed outcomes and tune from there
Typical stack
Frequently asked questions
Software that reads documents PDFs, scans, forms, emails and automatically extracts structured fields, classifies the document type, and routes it into the right workflow, replacing manual reading and data entry.
Yes, with the right OCR and extraction pipeline accuracy on scans depends heavily on image quality and document consistency, which is why we validate against your actual document set before committing to an accuracy target.
Low-confidence extractions route to a human reviewer instead of being silently accepted this is the difference between a system that's safe to deploy and one that quietly introduces errors. We build confidence thresholds into every extraction pipeline.