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Future AGI vs Langfuse

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 $250/mo for Future AGI
Free plan
Both have one
Public API
Both have one
Higher Trust score
Future AGI — 88 vs 80 for Langfuse
Best fit
Future AGI: Teams shipping customer-facing AI agents who need pre-launch testing · Langfuse: Engineering teams running LLM apps or agents in production who need traces and cost tracking

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

Future AGITesting and monitoring platform for AI agents, catching hallucinations before and after they ship.LangfuseOpen-source LLM engineering platform for tracing agents, versioning prompts, running evals and tracking cost, hosted or self-hosted.

Side by side

FactFuture AGILangfuse
CategoryLLM Observability & EvaluationLLM Observability & Evaluation
Pricing modelFreemiumFreemium
Starts at$250/mo$29/mo
Public APIYesYes
Trust score88 / 10080 / 100
PlatformsWeb, APIWeb, API
CompanyFuture AGI, Inc.Langfuse GmbH
Launched20242023
Last verifiedOct 15, 2026Oct 29, 2026

What our research says

Future AGI

Future AGI covers the full loop of testing, evaluating and monitoring AI agents in one place, which saves stitching together separate eval and observability tools. Pricing is usage-based and can get hard to predict once you're past the free credits, and the fixed add-on tiers exist mainly for compliance features enterprises need.

Pros

  • Combines simulation, evaluation, guardrails and monitoring instead of separate tools
  • Free tier includes real usage (credits, gateway requests, voice minutes) to test with
  • Framework integrations cover text, RAG and voice agent use cases

Cons

  • Usage-based pricing across six different meters makes cost forecasting harder
  • Compliance features (SOC 2, HIPAA, SSO) are locked behind $250-$2,000/month add-on tiers
  • No fixed mid-tier plan between pay-as-you-go and the $250/month add-on tier

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

Which one fits

Choose Future AGI if you need

  • Teams shipping customer-facing AI agents who need pre-launch testing
  • Engineers who want hallucination detection and tracing in one dashboard
  • Companies that need SOC 2 or HIPAA-grade retention on eval data

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

Future AGI vs Langfuse: the questions people ask

Is Future AGI cheaper than Langfuse?

On published entry prices, Langfuse starts lower — $29/mo against $250/mo for Future AGI. Entry price is the lowest paid plan as we last verified it; what each plan includes differs.

Does Future AGI or Langfuse have a free tier?

Both: Future AGI has a free tier, and Langfuse has a free tier.

Which has a public API, Future AGI or Langfuse?

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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