Helicone

Helicone is an open-source LLM observability platform built around simplicity and speed of setup. Its headline feature is how easy it is to start: often you just route your LLM calls through its proxy with a one-line change, and instantly you have monitoring of your requests, costs and latency — no heavy integration required. For developers who want visibility into what their AI app is doing and what it is costing, fast, Helicone gets you there in minutes.

It provides clean, useful dashboards for cost and usage monitoring, request logging, caching and other practical features, all with minimal effort. While it is less focused on deep tracing of complex chains and rigorous evaluations than some heavier tools, it nails the everyday operational need: understanding your LLM usage, spotting cost spikes, debugging requests and keeping an eye on performance. Because it is open source with a self-hosting option, you can keep your prompt and response data under your control, which matters for teams handling sensitive information.

Helicone suits developers who want the fastest, simplest path to LLM observability — monitoring costs, usage and latency without a complex setup — and is a popular alternative alongside tools like Langfuse, which lean more toward deep tracing and evals. A common pattern is starting with Helicone for instant visibility, then adding a deeper tool as your AI app grows in complexity. If you are building with LLMs and want to stop guessing about cost and behavior, Helicone is an easy, low-friction way to get the visibility every production AI app needs.