AgentOps: Evaluation, Guardrails & Observability

Prove your agents work, and keep them working: golden-dataset evals, regression tests, policy-as-code guardrails, tracing and cost budgets.

Agents are non-deterministic. The same prompt can take a different path tomorrow, and a model upgrade can quietly break a workflow. We make agent behaviour measurable and controllable so you can ship with confidence and catch regressions early.

What you get

  • Golden datasets and automated evaluations for answers, tool calls and trajectories
  • Regression testing for model upgrades and prompt changes
  • Guardrails and policy-as-code (OPA/Rego) enforced on every agent action
  • Tracing, latency profiling and token-cost budgets per workflow
  • Red-teaming for prompt injection and data leakage

Typical use cases

Model migrationPre-launch certificationCost overrun controlCompliance evidence

Technology we use

OPA / RegoOpenTelemetryLLM-as-judge evalsLangfuseArize PhoenixCost dashboards

From our work: In our own builds we found tool-calling IDE clients silently retrying failed calls and burning hundreds of thousands of tokens per prompt. Token budgets and tracing are now standard in every engagement.

Bring us the workflow that eats your team's week.

In a 30-minute call with a senior architect, you'll learn whether an agent can take it on, what it would cost to build and run, and how we'd prove it works.

Book a discovery call