AI agent observability that sees every decision.

LLM observability tracks model calls: prompts, tokens, latency and cost. Agent observability adds the plan, the tools called, the policy checks and the real-world action, so you can see what was decided and why.

Agent tracing records each step of an agent's run as a span in one trace, from planning to the final action, so you can follow and debug a full task across models, tools and other agents.

Task success, policy compliance, escalation and override rates, groundedness, cost per task and latency. Which ones gate autonomy depends on the decision the agent makes.

It is useful at scale when it is calibrated. We check judge scores against human reviewers and combine them with rule-based checks and real outcomes in your systems.

Yes. Agents that emit OpenTelemetry traces can be observed and evaluated. Policy enforcement and trust graduation need the agent's actions to run through ElixirClaw.

In your environment for VPC, on-prem and sovereign deployments, with retention and redaction rules you set. SaaS residency options are confirmed for your region during scoping.

Pricing depends on deployment and volume. Ask for a quote for your environment — often packaged with the platform or based on trace volume.