RAG Knowledge Platform
FastAPI/React source for document-grounded knowledge workflows.
Project walkthrough →The workflow we can scope
When answers are buried in internal documents or reporting depends on technical queries, a focused retrieval or data-questioning workflow may help. Model choice, execution cost and access boundaries need evaluation against your environment.
Possible project scope
- Document preparation and retrieval with source references
- Connect local or hosted models according to infrastructure constraints
- Design information access and query execution boundaries
- Define representative examples and acceptance criteria for answer evaluation
What helps scope the work?
Share the workflow, a non-confidential input/output example, user roles, deployment environment and required integrations. Timing and cost can be agreed once the scope is understood.
Related source examples
AI Query · .NET
Layered reporting backend with a React query workspace.
Project walkthrough →Persian NL2SQL
Schema retrieval and policy-aware question-to-SQL source.
Source and architecture →How does your project differ?
A portfolio example starts the discussion. Implementation for your data, environment and constraints needs its own agreed scope.