How quickly can this reach production?

Typical first production release is 8–12 weeks, assuming data access and a named business owner are in place at kickoff.

Does this require replacing existing systems?

No. We integrate with the systems of record you already run and add an AI layer with its own controls and observability.

How is quality measured?

Every release passes a golden-dataset evaluation with agreed thresholds, and production quality is monitored continuously against the same rubric.

Use case · RAG

Production retrieval with chunking strategy, reranking, evaluation and freshness SLAs.

Expected ROI: Answer accuracy raised above agreed thresholds
Deployment timeline: 8–12 weeks

The problem

Models answer confidently from the wrong context.

Business outcomes

Measurable cycle-time reduction within the first quarter
Auditable decision trail acceptable to risk and compliance
Adoption sustained past pilot through embedded enablement

Reference architecture

01Governed retrieval over approved enterprise sources
02Policy-enforced model gateway with routing and cost controls
03Evaluation harness with regression gates before every release
04Full prompt, response and tool-call audit ledger

Security considerations

Data never leaves the approved boundary; no training on enterprise data
Prompt-injection and exfiltration testing before production
Least-privilege tool permissions with human approval thresholds

Frequently asked

Next step

Deploy rag in your enterprise.

Sixty minutes with a Chief AI Advisor and a forward deployed engineer. We read your environment, name the blockers, and give you the shortest path to a system in production.

Book a working session Explore Capabilities