Three questions every AI agent owner should be able to answer.
What was asked?
What users really want from your agent: topics, intents and the recurring problems it can't handle yet.
What happened in between?
Every retrieval, tool call and model call traced, with its latency, cost and errors.
What was answered?
Response quality scored against your business metrics instead of gut feeling or random spot checks.
Every conversation traced from start to finish.
In this example, a customer asks to change the delivery address of their order. The trace shows what the agent did to answer: retrieval, planning, a tool call, the response and a privacy check, each with its latency, cost and quality scores.
Instrument once, see everything
We connect your agent to OpenTelemetry-compatible tracing without touching its logic. Every conversation is captured automatically.
Every step visible
Retrievals, model calls, tool calls and guardrail checks on a timeline. You see right away where time goes and which step failed.
Cost and quality side by side
Tokens, cost and automated evals for every response, so you can track quality and spend together.
What the example shows: formatting the response (llm.respond) takes 38% of total response time. A shorter context or a lighter model for this step would speed up the answer without lowering quality scores.
From instrumentation to dashboards.
We make sure measurement is reliable and continuous. You get a clear picture of how your agent performs.
Instrumentation
We connect your agent to OpenTelemetry-compatible tracing without changing the agent's own logic.
Trace analytics
Traces, observations, tool calls and RAG calls in one view. See where time, money and errors come from.
Context analysis
What the model saw when it answered: retrieved data, conversation history and instructions. We find missing and misleading context.
Customer insight
What users asked and what the agent answered. Topic clustering, trends and the blind spots where the agent falls short.
Cost optimisation
Know where your token budget goes and how to get the same quality at a lower cost.
Dashboards and alerts
Dashboards for leadership and developers, plus alerts when something drifts from normal.
A clear path to production.
A phased rollout where every phase has a clear outcome. At the end you have production monitoring and dashboards that are running, rather than a report on a shelf.
- Step 1
Discovery
The agent's architecture, use cases and definition of success, worked out with your team.
- Step 2
Instrumentation
Tracing goes live, and the first traces are visible straight away.
- Step 3
Analysis
We go through the traces: where the agent succeeds, where it falls short and what it costs.
- Step 4
Dashboards and handover
Dashboards, alerts and documentation. Your team can use them on their own.