Helicone's integration model is deliberately minimal: instead of wrapping every LLM call in a tracing SDK, it works as a proxy that sits between an application and a model provider, so adopting it is often just a matter of changing a base URL rather than instrumenting code throughout an application. Every request passing through gets logged with its cost, latency, and full request and response content.
That proxy-based approach makes it fast to adopt for teams that just want visibility into spend and performance without a larger observability integration project, though it trades off some of the deeper, framework-aware tracing that LangSmith or Langfuse offer for teams using LangChain or complex agent chains specifically.
Being open source and offering a generous free tier, it's a common first step for teams that want to answer how much they're actually spending on LLM calls and which ones are slow, before committing to a more involved observability setup, with self-hosting available for teams that don't want request data passing through Helicone's own infrastructure.