RAG you can put in production — and prove.
Retrieval-augmented generation is the fastest path to value from your own data and the fastest path to a leak. Kynexa governs retrieval and context assembly so RAG answers stay inside the lines.
The problem
RAG returns whatever is most relevant in the index, regardless of whether the person asking is allowed to see it. The model then blends those chunks into a confident answer, often with no record of what informed it. One ungoverned RAG app can expose salary data, contracts, customer records or strategy; through a perfectly innocent question.
How enforcement changes the workflow
Without governance
- Retrieves whatever is most relevant - regardless of permission
- Model blends chunks into a confident answer
- Often no record of what informed it
Kynexa enforces
- Filter, redact or annotate chunks by role, intent, sensitivity
- Assemble context under policy before the model sees it
- Ground answers with citations and lineage
With Kynexa
- Answers respect role, intent and sensitivity
- Every response cited and traceable
- Lower leakage risk and token cost
Audit evidenceRecords which chunks were considered, the policy applied and why context was included, denied or redacted.
What you get
Policy-aware retrieval and context assembly
Per user and per intent.
Citations and end-to-end lineage
On every answer.
Provider-agnostic models
Bring your own vector store.
Lower leakage risk and lower cost
From minimized context.
Outcome
A RAG application that passes security review the first time — accurate, cited, auditable.
See Kynexa govern your AI — in 30 minutes.
Bring a real use case. We'll set up governed retrieval, reasoning and audit on your stack.