1
LangSmith
LangChain's tracing, evals, and prompt management platform.
Pros
- +Deep LangChain/LangGraph integration
- +Strong eval suite
- +Datasets and feedback
Cons
- -Best on LangChain stack
- -Pricing tiers up fast
Best LLM Observability
LLM observability tools trace prompts, tool calls, and agent loops so you can debug regressions, compare models, and run evals. The space splits between dev-loop tracing and full eval/feedback platforms.
2
Langfuse
Open-source LLM observability with traces, evals, and prompt management.
Pros
- +Self-hostable
- +Framework-agnostic SDKs
- +Active OSS community
Cons
- -Self-hosting effort
- -UI denser than Helicone
3
Helicone
Drop-in proxy for OpenAI-style APIs with caching, logging, and rate limits.
Pros
- +One-line integration
- +Built-in caching
- +Open source
Cons
- -Proxy adds latency
- -Less eval tooling
4
Arize Phoenix
Open-source LLM tracing and eval tool from the ML observability company.
Pros
- +OpenTelemetry native
- +Strong eval primitives
- +Enterprise pedigree
Cons
- -Heavier than Helicone
- -Steeper ramp
5
Weights & Biases Weave
W&B's LLM tracing and evals layer, integrated with Models for full ML coverage.
Pros
- +Unified ML + LLM platform
- +Strong eval and dataset tools
- +Mature company
Cons
- -Overkill for tiny apps
- -Ecosystem-heavy
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