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AgentOps vs Langfuse

A side-by-side comparison of AgentOps and Langfuse, two Observability tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

AgentOps

Observability

Observability and tracing built for AI agents.

View AgentOps

Langfuse

Observability

Open-source LLM observability. Self-hostable, OpenTelemetry-native.

View Langfuse

At a glance

Feature comparison of AgentOps and Langfuse
AttributeAgentOpsLangfuse
CategoryObservabilityObservability
PricingFREEMIUMFREEMIUM
LicenseOpen coreOpen core
DeploymentHybridHybrid
Platforms (differs)Web, APIAPI, Web
Model supportModel-agnosticModel-agnostic
Vendor (differs)AgentOpsLangfuse

The honest brief

AgentOps

Purpose-built for multi-step agents — session replay with time-travel debugging and per-run cost tracking, not just flat LLM-call logging.

  • Open-source MIT SDK, two-line setup
  • 400+ LLM and framework integrations
  • Records every LLM call, tool use, decision
  • Agent benchmarking and evaluation
  • Free tier to start
  • Python/TypeScript SDK-centric
  • Full analytics rely on the hosted dashboard
  • Younger than general-purpose APM tools

Langfuse

The MIT-licensed, self-hostable answer to LangSmith — own your observability data, framework-agnostic.

  • Own your observability data
  • Framework-agnostic, OTel-native
  • Tracing + evals + prompt mgmt
  • Transparent unit-based pricing
  • Self-host infra cost at scale
  • Less deep LangChain integration
  • Setup heavier than hosted-only