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OpenLIT

Open-source alternative to LangSmith, Datadog LLM observability

OpenLIT is an open-source alternative to LangSmith and Datadog’s LLM observability tools for teams building AI apps. It tracks how your language models and AI agents behave, logs prompts, and helps you watch costs per request. Anyone shipping AI features can use it to see what their models are actually doing in production.

Best for: AI developers who need to monitor and trace LLM apps.

Key features

  • LLM observability and agent tracing
  • Cost tracking per request
  • Prompt management

Before you switch

Developer tools live or die by their community. Before switching, glance at recent commit activity, open issues, and documentation quality — a healthy project answers questions quickly. Most open-source dev tools install with a single command and play well with existing workflows, so you can trial one alongside your current stack. If your team depends on it daily, check the release cadence and whether commercial support is available.

Like every project on OpenShelf, OpenLIT is developed in the open — you can read the code, follow development, and even contribute. Check the system requirements and the project’s own documentation linked on this page before installing.