Solvin GraphRAG .
An answer is only useful if you can trace it.
Concept illustration / A view of the idea, not a product screenshot.
01 / The context
The problem
worth working on.
A company’s useful knowledge rarely lives in one document. Finding an answer can mean following relationships across manuals, policies, and revisions—and knowing which version to trust.
02 / The approach
How the pieces
come together.
- 01
Built a document-to-knowledge workflow with versioned sources, asynchronous ingestion, and a review step before extracted knowledge is published.
- 02
Combined keyword, semantic, and graph-assisted retrieval so relationships can enrich an answer without replacing direct source evidence.
- 03
Designed separate experiences for readers, knowledge managers, and administrators, with citations, answer traces, and usage oversight.
03 / A key decision
The detail
that shapes the system.
Keep the human review gate explicit. Uploading a document should not silently turn every extracted statement into approved company knowledge.
04 / The result
What came out of it.
A working MVP that brings retrieval, knowledge review, and administration into one product. The system supports configurable domains rather than one fixed document taxonomy.
Scope & limitations
The documented demo uses deterministic providers by default. Real model adapters are present, but this case study does not claim a validated production deployment.