Observability & traceability

Laminar

Apache-2.0 OpenTelemetry-native platform for AI agents that traces LLM calls, tool use, custom functions and parallel sub-agents, presenting runs as transcripts rather than span trees. It records and replays runs in a debugger, builds evaluation datasets from production traces, and runs evals in CI. No documented access control.

hybrid · generally available · Research snapshot 2026-09-06

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Where it fits

Observability & traceability · Evaluation & testing

Useful conversation with: AI engineer, Agent platform developer.

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Replay a recorded agent run in the debugger, swap the prompt, and show the side-by-side comparison plus the eval that would catch the regression in CI.

Capabilities and evidence

Support labels reflect the supplied research. Documentation and vendor claims are not independent product tests. “Not established” means the researcher did not find support; it does not prove a capability is absent.

Documented by provider

Laminar traces every LLM call, tool call and sub-agent an agent runs, supports agents working through hundreds of steps across parallel sub-agents, and presents each trace as a transcript of agent inputs, LLM turns, tool calls and sub-agents rather than a span tree.

Limit: Sessions, human feedback and cost/token telemetry are not stated on the overview page, though the repository lists cost and token count as captured trace data.

Source s1

Documented by provider

The debugger records a run and replays it, and the playground can replay any traced span with prompts or models swapped for side-by-side comparison; evals can be run against datasets locally or in CI to catch regressions before shipping.

Limit: Replay is a developer debugging affordance; nothing documents tamper-evident storage or retention of replayed runs.

Source s1

Documented by provider

The repository states Laminar is Apache-2.0 licensed under the lmnr-ai organization, offers OpenTelemetry-based automatic tracing powered by OpenLLMetry with two lines of code, captures trace input/output, latency, cost and token count, and documents self-hosting alongside the managed platform.

Limit: No audit logs, RBAC, SSO, retention or compliance features are stated; latest release listed predates 2026.

Source s2

Limitations to discuss

Sources

  1. Laminar overview · Laminar · official docs
    Access date reported by researcher: 2026-09-06
  2. lmnr-ai/lmnr: Laminar · GitHub / Laminar · official repository
    Access date reported by researcher: 2026-09-06

Listing does not imply partnership, supplier status, a working DutyGraph integration, or a compliance certification.

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