Weave suits teams building or operating production AI agents that need tracing, evaluations, interaction monitoring, or prompt comparisons.
Best AI Agent Observability Tools 2026
When you need visibility into AI agent activity, observability tools can be compared by the traces and session details they make available. Check agent framework support alongside prompt and tool tracing, session replay, and trace retention to understand what you can inspect and for how long. Cost tracking, deployment options, free-plan availability, and paid-from pricing add further comparison points. SigNoz, Agenta, and PetalTrace are among the named options, along with Traccia and TraceRoot. The right balance depends on what you need to review across agent sessions, how you plan to deploy, and which cost information you want to track. Use the listed capabilities and access details to weigh those needs.
Opik
Opik suits teams developing applications or agents that call an LLM and need to inspect, evaluate, and monitor their behavior.
WebWindowsMac+3SigNoz
SigNoz suits teams monitoring application and infrastructure telemetry across logs, metrics, traces and exceptions.
AndroidiPhone & iPadWeb+2Langfuse
Langfuse suits teams building AI agent applications that need tracing, prompt management, and evaluation tools.
WebLinuxAPI+1LangWatch
LangWatch suits AI teams working on agents, including developers, product owners, QA, and domain experts involved in evaluation workflows.
WebMacLinux+2OpenLIT suits developers who want to observe LLM applications, prompts, evaluations, and costs.
Agenta suits teams that want to create and operate AI agents across work tools, with cloud or self-hosted deployment options.
LangSmith suits teams developing AI agents that need evaluation, prompt tools, tracing, and production monitoring.
It is designed for cross-functional AI teams, including product managers who want to define and analyze evaluations without code and developers who use SDKs, a CLI, or…
Traccia suits teams that need to inspect agent runs, evaluate outputs, or enforce limits on calls.
VoltOps suits teams managing AI agents, from small teams using Core to larger teams with advanced needs on Pro.
It suits teams building or operating AI applications that need provider routing, request tracing, or cost visibility.
Braintrust is intended for teams running AI agents in production, from early-stage projects to enterprise deployments.
PetalTrace suits developers who need to inspect and compare AI agent workflows.
Laminar suits teams building AI agents that need to trace model and tool activity, investigate runs, or evaluate changes against datasets.
Respan suits startup and enterprise teams tracing workflows, evaluating agent behavior, and monitoring production AI systems.
Fiddler AI is aimed at enterprises managing AI agents and predictive applications at scale, including teams that need monitoring, guardrails, and audit evidence.
TraceRoot suits teams operating AI agents that want to detect production issues and investigate fixes against code and GitHub history.