7 Best Agent Tracing Tools (LangSmith, Langfuse, Phoenix)

Tracing, evaluation, and debugging for LLM applications.

LangSmith

L

Best when teams need to connect traces, datasets, experiments, and production monitoring around agent quality.

Open-source LLM engineering platform for tracing, evals, and prompt workflows.

Langfuse

L

Best when teams want self-hostable observability with datasets, scores, and prompt management in one stack.

Open-source LLM and agent tracing with built-in evaluation.

Arize Phoenix

AP

Best when the team needs observability that connects prompt debugging, agent traces, and evaluation in one open-source tool.

Evaluation-first platform for logging, scoring, and comparing agent runs.

Braintrust

B

Best when product and engineering teams need fast experiment comparison across prompts, models, and tool paths.

Open-source AI gateway and LLM observability with proxy-based tracing.

Helicone

H

Best when you want request-level cost, latency, and cache metrics by routing LLM traffic through one gateway.

OpenTelemetry-native observability for LLM and agent workloads.

Traceloop

T

Best when platform teams already run OpenTelemetry and want LLM spans in existing backends.

Agent observability with tracing, analytics, and simulation-style testing.

LangWatch

L

Best when teams want to monitor conversations and agent flows while iterating on guardrails and scenarios.

Open-source toolkit for tracing, evaluating, and iterating on LLM apps.

Weights & Biases Weave

WB

Best when ML teams already use W&B and want LLM traces, evals, and comparisons in the same experimentation culture.

Production LLM gateway with routing, guardrails, MCP support, and observability.

Portkey AI Gateway

PA

Best when production agents need a unified API gateway across 200+ LLM providers with built-in load balancing, fallbacks, caching, guardrails, and cost tracking.

Enterprise GenAI evaluation, observability, and protection platform.

Galileo

G

Best for compliance-heavy teams that need enterprise-grade evaluation, observability, and real-time guardrails in a unified platform.

A lightweight SDK for agents, tools, handoffs, and traces.

OpenAI Agents SDK

OA

Best when the team already standardizes on OpenAI models and wants the shortest path from prototype to observable agent workflow.

Stateful graph orchestration for controllable agents.

LangGraph

L

Best when agent behavior must be represented as explicit nodes, edges, state, and recovery paths.