An enterprise platform for evaluating, monitoring, and guarding AI agents and LLM applications, including real-time protection against unsafe outputs.
Analytics comparison
Splunk Agent Observability (formerly 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
| Splunk Agent Observability (formerly 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
Splunk Agent Observability (formerly 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 Splunk Agent Observability (formerly Galileo) sits higher on the pricing ladder (Enterprise). Splunk Agent Observability (formerly 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.
Still deciding between Splunk Agent Observability (formerly Galileo) and Langfuse?
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