langfuse and helicone
Both are open-source LLM observability platforms with overlapping core features (monitoring, evaluation, experimentation), making them direct competitors in the same market rather than complementary tools.
About langfuse
langfuse/langfuse
🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
Provides distributed tracing via SDKs (Python, JavaScript/TypeScript) that capture full LLM call chains with automatic context propagation, backed by ClickHouse for scalable analytics. Features a unified API surface for programmatic access to traces, evaluations, and datasets, enabling custom workflows and integration into existing MLOps pipelines alongside LangChain, LlamaIndex, and other frameworks.
About helicone
Helicone/helicone
🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
Operates as a reverse proxy AI gateway that intercepts requests to 100+ LLM providers through a unified OpenAI-compatible API, enabling intelligent routing and automatic fallbacks. Built on a microservices architecture with a Cloudflare Workers proxy layer for request interception, Express-based collection server (Jawn), ClickHouse for analytics, and Supabase for application data. Integrates with OpenAI, Anthropic, Gemini, LangChain, Vercel AI SDK, and supports self-hosting via Docker or Helm with optional async logging through OpenLLMetry.
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