The problem
Most retrieval stacks optimize for finding similar chunks. Production agents also need to know whether those chunks are still true, still authorized, still relevant, and still explainable.
Symptoms
Signals that the issue is happening in production, not just in a benchmark.
An answer was semantically plausible but based on old policy or ticket state.
A cached response crossed a tenant, role, namespace, or entitlement boundary.
The team cannot reconstruct which source, watermark, filter, or retrieval path produced a bad answer.
Strict workflows still silently fall back to stale or best-effort context.
How KyroDB solves
KyroDB solves this at the runtime boundary before prompt assembly.
KyroDB sits between the agent backend and existing stores as a context correctness runtime.
It returns a ContextPacket with items, omissions, warnings, status, trace id, provenance, and freshness proof.
It treats scope, freshness, and proof as serving requirements, not after-the-fact analytics.
When strict context cannot be proven, KyroDB blocks or degrades explicitly instead of pretending the result is safe.
Implementation
Practical steps for teams already using an agent backend, vector store, or RAG pipeline.
- 01
Keep embeddings and source records in your existing store.
- 02
Send retrieval requests with tenant, namespace, authorization scope, filters, and freshness mode.
- 03
Emit scoped change events or write through KyroDB when source knowledge changes.
- 04
Use traces, proof reports, and replay workflows to debug bad responses and prove what the runtime served.
When not to use it
If your product only needs a demo vector search over static public documents, a correctness runtime may be more machinery than you need.
Is context correctness the same as retrieval accuracy?
No. Retrieval accuracy asks whether the returned material is relevant. Context correctness also asks whether the material is fresh, scoped, traceable, and safe to use now.
Can context correctness reduce hallucinations?
It reduces hallucinations caused by stale, wrong-scope, polluted, or unprovable context. It does not eliminate every model hallucination.