
Langfuse
8.2#1 in prompting toolFrom $29 a monthFree planWebAPILinuxSelf-hosted
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| Fact | Langfuse | PromptLayer |
|---|---|---|
| Evaluation | Evaluation features include LLM-as-a-judge, code evaluators, user feedback, manual labeling, datasets, and experiments. | Evaluations can be triggered on new prompt versions, through the API, or ad hoc in the UI, and include historical backtests and side-by-side model comparisons. |
| Headquarters | Berlin, Germany; San Francisco, United States | PromptLayer says it is located in New York City. |
| Integrations | Langfuse lists more than 100 integrations spanning OpenTelemetry, Python and TypeScript, model providers, agent frameworks, gateways, and developer tools. | The LangChain integration exports traces through OpenTelemetry and supports cost and latency analytics, searchable metadata, and turning traces into evaluation datasets. |
| Observability | Hierarchical traces capture LLM calls, tool invocations, and retrieval steps, with filtering by user, session, cost, latency, and metadata. | PromptLayer tracks requests, traces, cost, latency, token usage, scores, and custom metadata, with OpenTelemetry span support. |
| Product | Langfuse is an open-source AI engineering platform that helps teams collaboratively debug, analyze, and iterate on AI agent applications. | PromptLayer combines a prompt registry and visual prompt CMS with LLM evaluations, observability, and agent tracing. |
| Prompt management | Prompt Management provides versioning, one-click deployments, rollbacks, prompt labels, and per-version performance metrics. | Teams can visually edit, version, test, and deploy prompts without waiting for an application redeploy. |
Langfuse suits teams building AI agent applications that need tracing, prompt management, and evaluation tools. It also supports teams that want to self-host the core on their own infrastructure.
PromptLayer suits engineers and domain experts who need to manage prompts and evaluate AI products together. Its enterprise hosting and access-control options may suit teams with specific deployment or governance needs.