Weave suits teams building or operating production AI agents that need tracing, evaluations, interaction monitoring, or prompt comparisons.
Best AI LLM Observability Tools 2026
When LLM-powered applications are in the picture, observability tools help you inspect request traces, investigate failures, and assess outputs and costs. Compare LLM trace capture with failure tracking and latency metrics to understand what you can monitor. Output evaluations and token cost tracking add ways to examine results and usage. Free-plan access, retention on that plan, and the paid starting price may also shape your choice. Arize AX, Langfuse, and Opik are among the options to consider, alongside W&B Weave and Agenta. Use the listed criteria to decide which monitoring signals and evaluation details matter for the applications you work with.
Opik
Opik suits teams developing applications or agents that call an LLM and need to inspect, evaluate, and monitor their behavior.
WebWindowsMac+3Langfuse
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
OpenLIT suits developers who want to observe LLM applications, prompts, evaluations, and costs.
WebWindowsMac+3Agenta 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…
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.
It is designed for engineers, QA teams, product managers, subject-matter experts, and annotators working on AI quality, evaluation, or production monitoring.
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.
Portkey suits teams building or operating applications that use multiple AI models and need routing, activity monitoring, and prompt management.
PromptLayer suits engineers and domain experts who need to manage prompts, evaluate changes, and observe AI product activity together.
Arize AX suits teams working to observe, evaluate, and improve AI agents in production.
Galileo is designed for engineers, product managers, and subject matter experts building AI applications.
Phoenix suits teams that need to inspect AI application traces and compare evaluation results across versions.