Product in development. Not generally available, not running in any production government environment, and not part of any capability we would put on a proposal today.
GenAI Context Engine
A memory and retrieval layer for GenAI systems that have to be auditable. The right document was not retrieved, the window was full of stale material, and nobody could explain the answer — we are fixing that at the infrastructure layer, the way feature stores fixed it for classical ML.
Architecture and current status
Ingest
Connectors, chunking and provenance capture at write time.
Context store
Structured and vector hybrid storage, versioned with rollback.
Retrieval & ranking
Tuned for relevance rather than raw similarity, with a freshness policy.
Agent / LLM runtime
Traceable generation with an evaluation harness in the loop.
Intended capabilities
Design targets for the first release. Not shipped features.
- Structured and vector hybrid storage for context and memory
- Retrieval and ranking tuned for relevance, not just similarity
- Full retrieval-and-generation traceability for every agent decision
- Versioned context artifacts with rollback
- An evaluation harness built in from day one
Deployment models under design
Intended targets. No accreditation of any kind is claimed today.
Cloud
Multi-tenant, for teams who want to move fast.
GovCloud
Isolated tenancy intended for federal workloads.
On-premises
Customer-hosted; no data leaves your boundary.
Air-gapped
Fully disconnected, for restricted environments.
Design partners
A small number of primes and enterprise teams with a concrete context problem, shaping the first release. Direct influence on the schema and the trace format, no obligation to adopt.
Contact us about the design partner program