Helicone vs LangSmith vs PromptLayer vs ModelWatch

Four different jobs. Helicone: drop-in proxy, logs every prod request, dashboards on cost, latency, error rate; great for OpenAI-style traffic. LangSmith: tracing for LangChain/LangGraph apps, prompt hub, offline dataset evals, human review queues. PromptLayer: prompt registry, version history, A/B testing of prompts. ModelWatch: continuous provider-side golden-prompt eval suite, public scorecards, alerts on model regression independent of your application code.

You do not pick one — they stack. Helicone or LangSmith for what your app is doing. PromptLayer for prompt change management. ModelWatch for what the model itself is doing under you. The cheapest mistake is assuming a prompt-analytics tool will catch silent model drift; it won't, because it has no fixed-input baseline to compare against.