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LLM Observability and Experimentation with Langfuse

Understanding what happens inside your LLM applications is critical for building reliable AI systems. We implement Langfuse—the leading open-source LLM engineering platform—to give you complete visibility into every interaction, from simple completions to complex multi-step chains. Langfuse provides end-to-end tracing that captures the full context of each request: prompts, completions, latency, token usage, and costs. But observability is just the beginning. With built-in experimentation capabilities, you can run A/B tests on prompts, compare model performance, and make data-driven decisions about your AI stack. Whether you are debugging unexpected outputs, optimizing for cost and latency, or systematically improving prompt quality, Langfuse gives you the tools to move from guesswork to engineering rigor. And because it is open-source and self-hostable, your sensitive data never has to leave your infrastructure.