Helicone

Helicone sits between an application and the model providers it calls, turning opaque LLM traffic into something inspectable. Changing the base URL in an OpenAI client is enough to start logging every request, and the same gateway reaches more than a hundred models behind one API key.

Beyond logging, the gateway handles routing and automatic fallbacks when a provider fails. Integrations cover OpenAI, Anthropic, Gemini, LangChain and the Vercel AI SDK, and metrics export to PostHog in a single line for teams keeping their dashboards elsewhere.

The platform gathers the tasks that follow a deployed model.

• Tracing: sessions and traces for agents, chatbots and document processing pipelines, inspectable when something goes wrong.
• Cost and latency: per-request accounting of spend, latency and quality across every provider in use.
• Playground: prompts, sessions and traces can be replayed and iterated on in the interface.
• Prompt management: versioning against production data, deployed through the gateway with no code change.
• Fine-tuning: handoff to partner services for training on the data already collected.

Self-hosting runs from a Docker Compose setup, with a Helm chart offered for enterprise workloads and manual deployment discouraged. The stack splits into a Next.js web frontend, a Cloudflare Workers proxy for logging, an Express server that collects logs, Supabase for the application database and auth, ClickHouse for analytics and MinIO for object storage. The hosted service is SOC 2 and GDPR compliant, with a free tier of ten thousand requests a month.