# See what your agent does and how well it serves your customers. > Agent observability: we trace every retrieval, tool call and model call and build dashboards that show your AI agent's quality, latency and cost in production. Page: https://semantly.fi/en/agent-observability Language: English Also in: [Suomi](https://semantly.fi/agenttien-tuotantoseuranta.md) We trace every retrieval, tool call and model call, with its latency, cost and errors. You get a clear picture of how the agent behaves and the dashboards to keep track of it. ## 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. 1. **Discovery.** The agent's architecture, use cases and definition of success, worked out with your team. 2. **Instrumentation.** Tracing goes live, and the first traces are visible straight away. 3. **Analysis.** We go through the traces: where the agent succeeds, where it falls short and what it costs. 4. **Dashboards and handover.** Dashboards, alerts and documentation. Your team can use them on their own. ## Other services - [From pilot to production](https://semantly.fi/en/pilots-to-production.md): A partner that takes your AI pilot reliably into production, with quality, security and monitoring in place. - [Evals and guardrails](https://semantly.fi/en/evals-and-guardrails.md): Automated quality scoring and systematic testing against misuse. - [MCP servers and MCP Apps](https://semantly.fi/en/mcp-servers.md): Your product's data and actions inside AI assistants, with interactive views. --- Semantly (Screenful Oy, Helsinki). Contact: hey@semantly.fi ยท [Book an assessment call](https://semantly.fi/en/contact)