Platform
Four layers between your agent and an incident.
Tracing, evals, guardrails and audit — four layers on one data model, deployable in your own cloud.
01
Observe
Tracing
Every agent run captured as a replayable trace — prompts, tool calls, retrievals and outputs, linked to the user and the model version.
100%
of agent runs captured and replayable
→
02
Measure
Evals
Regression suites that score every prompt, model and tool change against your own graded cases — before a single customer sees it.
3,400
graded cases in a typical bank suite
→
03
Protect
Guardrails
Inline policy checks on every response — PII, jailbreaks, off-policy advice and hallucinated facts — in under 40 ms at the p95.
38 ms
p95 added latency per checked response
→
04
Prove
Audit
Evidence packs mapped to model-risk policy and the EU AI Act — every test, threshold and incident, exportable on demand.
2 days
typical model-risk review, down from 3 weeks
→
02 // The loop
One loop from first trace to signed-off release.
01
Instrument
SDK, spans and replay for every agent run.
02
Evaluate
Graded suites on every prompt and model change.
03
Guard
Inline policy checks before output ships.
04
Audit
Evidence packs your regulator can read.
Ship the agent. Keep the evidence.
Send us an agent, a failure or a policy. An evaluation engineer replies within one working day.