LLM Observability Without LangSmith: Five Open-Source Tools Compared
At some point in building LLM applications or agents, you need to know why a call failed, what the tool invocation looked like, or why the agent got stuck in a loop. LangSmith, LangChain’s commercial observability platform, has been the default answer for this: it covers trace visualization, prompt versioning, and evaluation in one place. Its usage-based pricing and cloud-hosted architecture are where teams start looking for alternatives.
Read MoreFuture AGI: Evaluate, Observe, and Improve AI Agents in One Place
If you have shipped an AI agent, this will sound familiar. The demo runs fine. Then it hits production, the hallucinations start, and you can’t tell what went wrong or why. So you bolt on one tool for evals, another for tracing, another for guardrails. The real problem is that none of them talk to each other, so the loop you need to actually fix things never closes.
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