Langfuse
Generative AI infrastructure software
Generative AI software
- Features
- Ease of use
- Ease of management
- Quality of support
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$29 per month
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Free version
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- Information technology and software
- Banking and insurance
- Healthcare and life sciences
What is Langfuse
Langfuse is an observability and evaluation platform for applications built with large language models (LLMs). It helps engineering and data teams capture traces, prompts, responses, costs, and user feedback to debug, monitor, and improve LLM-powered features in production. The product typically integrates via SDKs and APIs and supports workflows such as prompt iteration, dataset creation from production logs, and experiment/evaluation tracking. It is commonly deployed as a managed service or self-hosted, depending on organizational requirements.
LLM tracing and observability
Langfuse captures end-to-end traces for LLM calls, including prompts, responses, metadata, and latency. This supports root-cause analysis for quality regressions and production incidents in AI features. The trace-centric model aligns with how teams debug multi-step agent and retrieval-augmented generation (RAG) pipelines. It also enables ongoing monitoring rather than one-off testing.
Evaluation and feedback workflows
Langfuse supports collecting human feedback and structuring production interactions into datasets for evaluation. Teams can compare prompt or model variants and track changes over time using experiment-like workflows. This helps operationalize quality measurement beyond ad hoc manual review. It is useful for organizations that need repeatable evaluation processes for LLM outputs.
Flexible deployment options
Langfuse offers self-hosting options in addition to hosted usage, which can fit data residency and security constraints. This is relevant for regulated environments that cannot send prompts or user data to third-party SaaS without controls. Self-hosting also allows tighter integration with internal logging, identity, and network policies. The product’s API/SDK approach supports integration into existing application stacks.
Not an end-to-end builder
Langfuse focuses on observability and evaluation rather than providing a full environment to design, orchestrate, and deploy complete AI applications. Teams still need separate components for model hosting, vector search, data preparation, and application runtime. Organizations looking for a single integrated platform may need additional tools. This can increase integration work for smaller teams.
Data governance depends on setup
Because Langfuse logs prompts, responses, and metadata, teams must actively configure redaction, retention, and access controls to meet privacy requirements. If sensitive data enters prompts, it can be captured in traces unless mitigations are implemented. Self-hosting reduces third-party exposure but shifts responsibility for security operations to the customer. Governance maturity becomes a prerequisite for broad rollout.
Evaluation remains context-specific
LLM quality metrics and test sets are highly dependent on domain, language, and task design, and Langfuse does not eliminate the need for careful evaluation design. Teams may need to build custom scoring, labeling guidelines, and gold datasets to get reliable signals. Automated evaluation can be noisy for open-ended tasks and may require human review loops. This can limit immediate ROI for organizations without dedicated AI/ML operations capacity.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Hobby | Free | All platform features (with limits); 50k units/month included; 30 days data access; 2 users; community support via GitHub; no credit card required. |
| Core | $29 per month | 100k units/month included; $8 per 100k units overage (graduated volume discounts available); 90 days data access; unlimited users; in-app support. |
| Pro | $199 per month | 100k units/month included; $8 per 100k units overage; 3 years (\u002b) data access (unlimited history); unlimited annotation queues; high ingestion/rate limits; SOC2 & ISO27001 reports; BAA (HIPAA) available; prioritized in-app support. |
| Teams (optional add-on) | $300 per month | Optional add-on for Core/Pro: Enterprise SSO (Okta, AzureAD), SSO enforcement, fine-grained RBAC, dedicated Slack channel support, data retention management. |
| Enterprise | $2,499 per month | Everything in Pro + Teams; 100k units/month included; $8 per 100k units overage (volume discounts available); audit logs; SCIM API; custom rate limits; uptime & support SLAs; dedicated support engineer; custom billing (AWS Marketplace or invoice); contact sales for terms. |
| Self-hosted (Open Source) | Free | MIT-licensed self-hosted distribution: all core platform features and APIs; unlimited included usage; deployment docs/Helm; community support; optional Enterprise paid add-ons for support, management APIs, and compliance. |
