← All selected work
AI product engineering
Secure multi-tenant AI document review
A full-stack platform that turns OCR and model output into an inspectable review workflow instead of a black-box answer.
Primary evidenceEnd-to-end
architecture and delivery
Situation
What the system needed to change
A document-heavy product needed secure tenant boundaries, automated processing, versioned source files, and an interface where reviewers could see AI output in context.
Constraints
The boundaries mattered.
- 01
Authentication and authorization had to inform the data model
- 02
Storage could not be tied to a single provider
- 03
Reviewers needed to inspect OCR and model output directly on documents
Decisions
The important engineering choices
- Designed a Fastify service exposing GraphQL and REST around PostgreSQL
- Used Auth0 identity to drive tenant-aware access and row-level security decisions
- Separated versioned object storage from document-processing orchestration
- Built the Next.js review interface and production delivery path to AWS
Outcome
What the work left behind
- A secure full-stack foundation for AI-assisted document review
- Inspectable model output rather than untraceable generated text
- Containerized deployment through GitHub Actions