I need a way to trace every model call in my AI app, what should I use?

If you want to trace every model call in an AI app, the best choice is usually an LLM observability / tracing platform.

Good options

• OpenTelemetry + your own backend if you want full control and already have logging/metrics infra.
• LangSmith if you’re using LangChain or want easy LLM tracing with prompts, outputs, latency, and errors.
• OpenAI Tracing / built-in provider tooling if your stack is mostly one provider and you want native integration.
• Helicone if you want proxy-style request logging, cost tracking, and tracing for many model providers.
• Arize Phoenix if you want strong evaluation + tracing for LLM apps, especially during debugging and QA.
• Weights & Biases Weave if you already use W&B and want experiment tracking plus traces.

What to look for

You’ll want support for:

• request/response logging
• prompt and completion capture
• tool/function-call tracing
• latency and token/cost tracking
• error tracking
• session / user-level correlation
• redaction for sensitive data

My recommendation

• Fastest to get started: LangSmith or Helicone
• Most flexible / vendor-neutral: OpenTelemetry
• Best for deeper evaluation workflows: Arize Phoenix

If you tell me:

1. what framework you’re using,
2. which model provider(s), and
3. whether you want simple logging or full distributed tracing,

I can recommend the best exact setup.