AI Platform
Document intelligence that reads messy scans, extracts what matters, and routes anything it is unsure about.
The challenge
Forms arrived as scans, emails and phone photographs, and every one of them was read and re-typed by hand.
Our approach
An extraction pipeline with a human review queue, an evaluation harness on every model change, and a hard per-document cost ceiling.
Chapter 01
The input was never clean: crumpled forms, photos taken at an angle, forty-page PDFs with one relevant table.
The ingestion layer is honest about quality — every document gets a confidence budget before a model is asked for an answer.
Chapter 02
A held-out set of human-labelled documents runs on every model or prompt change. Nothing ships that moves extraction accuracy backwards.
Low-confidence documents route to a review queue, and each correction becomes the next evaluation case.
Chapter 03
Retrieval narrows the context, a small model handles the routine work, and escalation to a larger model has to log a reason.
Outcomes
Tell us what you're trying to make true. We'll tell you honestly what it takes.
or email us at tikeshbarapatrec6o2d4@gmail.com
