Multi-source retrieval
Ingest PDFs, docs, HTML and databases into one searchable corpus with provenance on every chunk, so answers trace back to a real source.
← RAG & enterprise search portfolio
·RAG & enterprise search · reference example
Docs-grounded support that cites its sources — like Inkeep
Inkeep is a docs-grounded AI support assistant for product documentation. It's a recognisable benchmark for a system class I build — here's what it does, and how I'd build yours.
Reference example — not my client. Inkeep is an independent product I'm not affiliated with, shown as a benchmark for this kind of build.
Live preview of www.inkeep.com — their site, shown as reference.
01What a Inkeep-class system does
The shape of the build
At its core, Inkeep is a docs-grounded AI support assistant for product documentation — the kind of system you reach for when you have support deflection and citation-backed answers. Here is how I'd build one for you.
Permission-aware by design
Retrieval is scoped to what each user is cleared to see — a query can't reach a document it shouldn't, no matter how it's phrased.
Hybrid search + rerank
Dense vectors catch paraphrase, keyword search catches the exact identifier, and a reranker keeps only the strongest evidence.
Grounded, cited answers
Every claim resolves to the chunk it came from, with a refusal path when the evidence isn't there.
02More RAG & enterprise search examples
Other benchmarks in this class
Same system class, different products. Each opens a page like this one.
Want something like Inkeep?
Tell me what it needs to do and where it's getting stuck. I'll tell you honestly whether I'm the right person and what it would take — no pitch deck, no discovery call to book a discovery call.