GalileoEnterprise
An enterprise platform for evaluating, monitoring, and guarding AI agents and LLM applications, including real-time protection against unsafe outputs.
Analytics comparison
Galileo vs Langfuse
Pricing, pros, cons, and ideal use cases — side by side.
LangfuseFreemium
An open-source observability and evaluation platform for LLM applications — tracing, prompt management, evals, and cost monitoring.
At a glance
| Galileo | Langfuse | |
|---|---|---|
| Pricing | EnterpriseEnterprise pricing, quoted per organization. | FreemiumOpen-source and free to self-host. Langfuse Cloud offers free and paid managed tiers. |
| Category | Analytics | Analytics |
| Ideal for | Enterprises running agents and LLM apps at scaleRegulated organizations needing runtime safeguardsTeams needing both evaluation and live monitoring | Teams running LLM apps and agents in productionEnterprises needing self-hosted observabilityEngineering orgs standardizing AI tracing and evals |
Pros & cons
Galileo
Pros
- Evaluation, monitoring, and runtime guardrails in one platform
- Real-time detection of unsafe or off-policy outputs
- Metrics that work without ground-truth labels
- Built for enterprise scale
Cons
- Enterprise pricing and procurement
- More than small teams or simple apps need
- Onboarding is a real implementation effort
Langfuse
Pros
- Full tracing for LLM and agent applications
- Open-source and self-hostable for data residency
- Prompt management, evals, and cost analytics
- Framework-agnostic
Cons
- Self-hosting adds operational work
- Eval design is still real effort
- Trace volume can grow storage needs at scale
Which should you choose?
Langfuse is the lighter-weight option (Freemium), while Galileo sits higher on the pricing ladder (Enterprise). Galileo is built around enterprises running agents and llm apps at scale; Langfuse leans more toward teams running llm apps and agents in production. Shortlist the one whose strengths line up with your biggest constraint.