Observe every agent decision.
We build full observability for AI agents: end-to-end traces, policy guardrails, audit-ready logs, and explainability outputs that help teams trust production behavior.
Need deployment context too? Explore our integrations and security model.
Tracing
Correlate prompts, tool calls, external APIs, retries, and outputs per run with structured root-cause visibility.
Guardrails
Apply input/output policy checks, tool permission boundaries, and escalation gates for high-risk actions.
Logs & Audit
Maintain immutable event logs with actor, action, context, and timestamp metadata for compliance and incident response.
Explainability
Expose decision summaries, evidence references, and review artifacts without leaking hidden chain-of-thought internals.
Tools we integrate for observability
Vendor-agnostic integrations across tracing, evaluation, orchestration, and operational monitoring stacks.
LangSmith
Agent tracing, live dashboards, and alerts for latency, quality, and cost.
Langfuse
OTEL-friendly trace capture, eval loops, and production debugging workflows.
Arize / Phoenix OSS
Tracing + evaluation pipelines with monitoring and model behavior analytics.
Monte Carlo
Data + agent observability to connect context quality with agent behavior.
Camunda
Process-level orchestration telemetry for human + AI execution paths.
Tines / Boomi
Workflow automation and enterprise integration telemetry for cross-system reliability.
Closed-loop reliability workflow
Instrument
Capture traces and logs across prompt, retrieval, tool, and execution layers using consistent schemas.
Evaluate
Run online and offline evals for quality, drift, hallucination risk, and guardrail adherence.
Improve
Feed production learnings back into prompts, tools, policies, and orchestration logic with regression checks.
Ready to agentify your org chart?
Let's discuss how we can build custom AI agents that automate your workflows, reduce costs, and scale your operations.