AgentOps
7.8#7 in ai agent observability toolsFrom $40 a monthFree planWebAPISelf-hosted
VisitAgentOps vs Langfuse
What both publish
| Fact | AgentOps | Langfuse |
|---|---|---|
| Documentation | Documentation includes quickstarts, integration guides, examples and self-hosting instructions. | Documentation covers observability, prompt management, evaluation, metrics, APIs, SDKs, integrations, compatibility, deployment, and security with versioned self-hosting guides. |
| Headquarters | Delray Beach, Florida, United States | Berlin, Germany; San Francisco, United States |
| Licence | The AgentOps application and repository are released under the MIT licence. | Langfuse states that all product features are MIT licensed, while a separate Enterprise license covers governance features such as project RBAC, audit logs, SCIM, and retention policies. |
| Product | AgentOps describes itself as a developer platform for building AI agents and LLM apps, with observability for OpenAI, CrewAI, AutoGen, and 400+ LLMs and frameworks. | Langfuse is an open-source AI engineering platform that helps teams collaboratively debug, analyze, and iterate on AI agent applications. |
| Rating on G2 | 0.0 out of 5 from 0 reviews | 4.5 out of 5 from 1 review |
| SDKs | The documentation says AgentOps is available for Python and TypeScript/JavaScript applications. | Official SDKs are Python v5 and JavaScript/TypeScript v6; other languages can use OpenTelemetry instrumentation. |
| Self-hosting | The repository documents running the full dashboard and API backend on a user's own machine, while the enterprise plan lists AWS, GCP and Azure self-hosting. | The OSS edition can be deployed with Docker Compose, Kubernetes Helm, or Terraform guides for AWS, GCP, and Azure, including offline or air-gapped installations. |
AgentOps plans
- BasicFree
- Pro$40 a month
- EnterprisePriced on request
Langfuse plans
- HobbyFree
- Core$29 a month
- Pro$199 a month
- Teams Add-on$300 a month
- Enterprise$2,499 a month
Pick AgentOps if…
It suits engineers building and scaling AI agents who need tracing, replay debugging, cost monitoring, and execution records. Teams can use web access, an API, or self-hosting.
Pick Langfuse if…
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.