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Langfuse vs Rhesis AI

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan
Both have one
Public API
Both have one
Best fit
Langfuse: Engineering teams running LLM apps or agents in production who need traces and cost tracking · Rhesis AI: Teams that want product or domain experts writing test scenarios directly
Trust score
About even — Langfuse 80, Rhesis AI 82
Status
Both up at our last check — Langfuse Oct 29, 2026, Rhesis AI Oct 15, 2026

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

LangfuseOpen-source LLM engineering platform for tracing agents, versioning prompts, running evals and tracking cost, hosted or self-hosted.Rhesis AIOpen-source workspace where domain experts and engineers build test sets for AI agents together.

Side by side

FactLangfuseRhesis AI
CategoryLLM Observability & EvaluationLLM Observability & Evaluation
Pricing modelFreemiumFreemium
Starts at$29/mo—
Public APIYesYes
Trust score80 / 10082 / 100
PlatformsWeb, APIWeb, API
CompanyLangfuse GmbHRhesis AI GmbH
Launched2023—
Last verifiedOct 29, 2026Oct 15, 2026

What our research says

Langfuse

Langfuse is a strong default for teams that want tracing, prompt versioning and evaluations in one open-source tool, with the option to keep data on their own infrastructure. Teams that only want a hosted logging proxy with no SDK work, or that need guaranteed enterprise SSO without paying for add-ons, may find simpler or more bundled options.

Pros

  • MIT-licensed core that can be self-hosted without usage limits
  • Covers tracing, prompt management, evaluation and dashboards in one product
  • Generous free cloud tier and unlimited users from the $29 Core plan
  • OpenTelemetry support and SDKs for Python and JavaScript

Cons

  • Usage above the included 100k units is billed extra, so busy apps pay more than the headline price
  • Free tier keeps only 30 days of data and two users
  • Enterprise SSO and RBAC require the $300 Teams add-on on Pro or the Enterprise plan

Rhesis AI

Rhesis is worth a look for teams that want domain experts, not just engineers, writing test cases for an AI agent, and who are comfortable self-hosting an open-source tool. The MIT-licensed core is genuinely free, but anything past the community tier requires talking to sales since Enterprise pricing isn't posted.

Pros

  • MIT-licensed and self-hostable, not just a hosted demo
  • Supports UI, SDK, and MCP access for different kinds of users
  • Polyphemus red-teaming agent checks for jailbreaks and PII leaks specifically
  • Integrates with common agent frameworks via OpenTelemetry instrumentors

Cons

  • Enterprise pricing is not published anywhere
  • Self-hosting the open-source edition requires your own infrastructure and setup time

Which one fits

Choose Langfuse if you need

  • Engineering teams running LLM apps or agents in production who need traces and cost tracking
  • Organisations that must self-host observability data for compliance
  • Teams that want prompts, datasets and evals tied to the same traces

Choose Rhesis AI if you need

  • Teams that want product or domain experts writing test scenarios directly
  • Engineering teams already using OpenTelemetry-based tracing
  • Anyone needing a self-hostable, open-source eval platform

Langfuse vs Rhesis AI: the questions people ask

Is Langfuse cheaper than Rhesis AI?

Langfuse starts at $29/mo. Rhesis AI has a free tier; what its paid plans cost is not confirmed by us yet.

Does Langfuse or Rhesis AI have a free tier?

Both: Langfuse has a free tier, and Rhesis AI has a free tier.

Which has a public API, Langfuse or Rhesis AI?

Both ship a public API, so either can be built on; the fact table above shows the platforms each one runs on.

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