Document automation
Document automation turns files into structured, reviewed data that can move through software systems.
What the first version should do
A useful first version extracts fields, shows source evidence, flags low-confidence values, and exports approved records to the next system.
- Field extraction
- Source evidence
- Human review queue
- CSV, API, database, or queue export
Human review by default
For sensitive AI workflows, the system should show source evidence, confidence, suggested actions, and an approval path before anything important is sent or changed.
- Source citations
- Confidence and fallback handling
- Approval history
- Logging for AI actions
Production-minded delivery
A useful AI sprint is not a prompt demo. It needs data boundaries, user roles, retries, monitoring, security assumptions, and a clear path to integration.
- Data-source definition
- Role-based access assumptions
- API and model-provider assumptions
- Deployment notes