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Langfuse vs Tessl

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

Cheaper paid plan
Langfuse — $29/mo vs $100/mo for Tessl
Free plan
Both have one
Public API
Langfuse has one; not confirmed by us for Tessl
Best fit
Langfuse: Engineering teams running LLM apps or agents in production who need traces and cost tracking · Tessl: Engineering organisations standardised on Claude Code, Cursor or Copilot at scale
Trust score
About even — Langfuse 80, Tessl 81

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

Side by side

FactLangfuseTessl
CategoryLLM Observability & EvaluationPrompt Management & Versioning
Pricing modelFreemiumFreemium
Starts at$29/mo$100/mo
Public APIYesNot confirmed
Trust score80 / 10081 / 100
PlatformsWeb, APIWeb
CompanyLangfuse GmbHTessl AI Ltd
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

Tessl

Once a team standardises on coding agents, skills sprawl and nobody knows which ones help or whether any of them are safe. Tessl is the control layer for that: a scanned, versioned registry with evaluation attached, and the distinction between published skills and skills agents actually activate is a genuinely useful metric. The risk is that it governs a convention the ecosystem is still inventing.

Pros

  • Security scanning on skills before they reach an agent, which a plain public registry does not do
  • Evaluation tells you whether a skill actually helped instead of assuming it did
  • Separates skills that are published from skills agents genuinely activate
  • Free tier includes 1,000 credits a month and needs no card

Cons

  • Credits are the billing unit and the credit-to-work conversion is not published
  • Only useful if your team has already standardised on agents like Claude Code, Cursor or Copilot
  • $100 a month is a large step from free for a fivefold credit increase
  • No founding year, headcount or funding total is published on the site

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 Tessl if you need

  • Engineering organisations standardised on Claude Code, Cursor or Copilot at scale
  • Platform teams that need policy and security review over agent skills
  • Teams who want evidence a skill improves output rather than assuming it does

Langfuse vs Tessl: the questions people ask

Is Langfuse cheaper than Tessl?

On published entry prices, Langfuse starts lower — $29/mo against $100/mo for Tessl. Entry price is the lowest paid plan as we last verified it; what each plan includes differs.

Does Langfuse or Tessl have a free tier?

Both: Langfuse has a free tier, and Tessl has a free tier.

Which has a public API, Langfuse or Tessl?

Langfuse ships a public API, as of our last verification. A public API for Tessl is not confirmed by us — check its developer docs before you plan an integration.

Browse all LLM Observability & Evaluation →