Weave suits teams building or operating production AI agents that need tracing, evaluations, interaction monitoring, or prompt comparisons.
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Best LLM Observability Tools 2026
When you need visibility into how language-model applications behave, compare what each tool can trace and evaluate. Compared on agent tracing, LLM tracing, and retrieval tracing, these entries also cover LLM evaluations, prompt management, and token cost tracking. Deployment options, free-plan availability, and paid-from pricing can help you assess operational fit and cost. Arize AX, Evidently AI, and Helicone are among the named options, alongside Laminar, Langfuse, OpenLIT, Opik, and Respan (formerly Keywords AI). Consider which signals matter in your workflows, how you want to deploy a tool, and whether its listed evaluation and prompt features suit the way you build and oversee LLM-powered software.
Evidently AI
Evidently AI suits teams evaluating or monitoring language models, RAG applications, agents, or predictive ML workflows.
WebWindowsMac+3Opik
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 suits developers who want to observe LLM applications, prompts, evaluations, and costs.
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…
Promptfoo is for developers and enterprises building AI applications who need prompt evaluation or red-team testing.
It suits teams assessing conversational AI agents for safety and quality issues before production.
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.
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.
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.
Parea suits teams developing LLM applications that need evaluation, production observability, and human review.
Phoenix suits teams that need to inspect AI application traces and compare evaluation results across versions.