AI Engineer
ADA Document Remediation Engine
A multi-critic document remediation engine in Python, with audit-logged quality-assurance loops.
There is no public URL for this one. The write-up below covers the architecture and the decisions behind it, and we can walk you through it on a call.
A working Python pipeline that ingests structured PDF input plus embedded media, classifies each document to a DocumentProfile, and runs text, table, and structure critics in parallel to evaluate AI-assisted remediation. An audit logger records differences between quality-assurance loops so model decisions can be inspected.
The problem
AI-generated document remediation fails silently when the output is just text. Without parallel critics evaluating different aspects of the output, errors that are obvious to a human (a malformed table, a broken heading hierarchy, lost alt text) slip through. Single-pass remediation also makes it impossible to tell why a given model output was accepted or rejected when something goes wrong downstream.
What we built
The engine is a Python pipeline that classifies each input document to a DocumentProfile, then runs three critics in parallel (text, table, structure). Each critic evaluates the AI-generated remediation against its own criteria. An audit logger captures the diff between QA loops so every model decision is inspectable after the fact.
What was delivered
- Python remediation engine with DocumentProfile classification at the entry point
- Three parallel critics (text, table, structure), each with its own evaluation criteria
- Audit logger capturing diffs between QA loops so every model decision is inspectable
- Reusable architectural pattern for image-and-data-to-generated-content work
Outcomes
- Separate text, table, and structure checks before the output stage
- Every model decision is inspectable through the audit log
- Parallel critic structure ports to adjacent generation pipelines without redesign
- Eval discipline that separates a demo from a system a team can ship
Services: Python, AI document remediation, Multi-critic eval, Audit logging, PDF + media pipeline