AI-Assisted Document Pipeline
Signal is a concept for high-volume document intake — contracts, claims, applications — where language models do the first pass and humans review the uncertain cases.
The challenge
The hard part of applied AI is not extraction, it is calibration. A system that is confidently wrong is worse than no system. The concept focused on making uncertainty visible and routing it to a person.
Our approach
Every extracted field carries a confidence signal and a link back to its source span in the original document. Reviewers verify rather than re-key. Low-confidence extractions escalate automatically.
Design & development
A review queue ordered by uncertainty, side-by-side source and extraction panes, and an evaluation harness that tracks accuracy per field type over time so regressions surface before users find them.
Technologies
- Next.js
- Python
- Claude API
- PostgreSQL
Outcomes
This is a concept piece, so there are no production metrics to report. We publish outcome figures only when a client has verified and approved them.
Forma
Editorial Web Experience
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