Langfuse delivers Fortune 50-proven LLM observability with unmatched flexibility: full open-source self-hosting, unlimited users on paid plans, comprehensive compliance features, and enterprise-grade capabilities starting at $29/month - the strongest value for production AI teams.
Leading open-source LLM observability platform for production AI applications. Comprehensive tracing, prompt management, evaluation frameworks, and cost optimization with enterprise security (SOC2, ISO27001, HIPAA). Self-hostable with full feature parity.
Open-source LLM observability platform that shows exactly what your AI applications are doing - comprehensive tracing, prompt management, evaluation, and cost tracking with enterprise security.
Langfuse transforms black-box AI applications into transparent, debuggable, and optimizable systems through comprehensive observability, evaluation, and prompt management capabilities. Unlike basic logging tools, Langfuse provides enterprise-grade LLM engineering infrastructure that scales from hobby projects to production deployments processing millions of traces.
Deploy the same infrastructure powering Langfuse Cloud on your own systems with Docker Compose, Kubernetes (Helm), or Terraform modules for AWS, Azure, and GCP. Architecture requires PostgreSQL, ClickHouse, Redis/Valkey, and S3-compatible storage but delivers unlimited traces with zero usage costs.
Enterprise advantage: Full data residency, air-gapped deployments, and custom modifications while maintaining upgrade compatibility.Native integrations require minimal code changes:
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Langfuse stands as the definitive open-source LLM observability platform, combining enterprise-grade capabilities with unmatched deployment flexibility. The ClickHouse acquisition (2026) has accelerated development while preserving the open-source foundation that Fortune 50 companies trust. Unlimited users on paid plans, comprehensive compliance features, and full self-hosting capability make it the clear choice for production AI teams seeking observability without vendor lock-in.
Captures complete execution trees of complex AI workflows including multi-agent conversations, tool calling sequences, and RAG pipelines. Each trace shows parent-child relationships between all operations, enabling deep debugging of agent interactions and workflow bottlenecks with full context preservation.
Use Case:
Debug a customer support agent that gives incorrect answers by tracing the exact knowledge retrieval → context filtering → prompt construction → model generation → response formatting chain to identify the failure point.
Enterprise-grade prompt lifecycle management with version control, production trace linking, A/B testing capabilities, and protected deployment labels. Prompts are managed in the UI and linked to real production performance, enabling data-driven optimization without code deployment.
Use Case:
Test a new system prompt for a financial advisor agent by deploying two prompt versions simultaneously and comparing success rates, compliance scores, and customer satisfaction metrics in real-time dashboards.
Comprehensive quality assurance combining automated LLM-as-judge evaluators, categorical scoring, human annotation queues with inline comments anchored to specific text, and experiment management. Build regression datasets from production data for continuous model validation.
Use Case:
Implement systematic quality control for a medical AI assistant by running automated safety evaluations on every response and routing concerning outputs to medical professionals for detailed review with inline annotation tools.
Complete security package including SOC2 Type II, ISO27001, HIPAA compliance with BAA, enterprise SSO (Okta, Azure AD), SCIM API, audit logs, RBAC, and data retention management. Self-hosted option provides air-gapped deployment with full feature parity.
Use Case:
Deploy LLM observability for a healthcare organization requiring HIPAA compliance by using self-hosted Langfuse with encrypted data storage, access controls, and complete audit trails for regulatory reporting.
Granular cost tracking across multiple LLM providers with support for tiered pricing models (context-dependent rates for Claude, Gemini). Provides per-model, per-user, per-feature cost analysis with trend monitoring and budget alerting.
Use Case:
Optimize a multi-model AI application by analyzing cost-per-quality metrics across OpenAI GPT-4, Claude Sonnet, and local models to determine the optimal model routing strategy for different types of user queries.
Complete on-premises deployment using the same infrastructure as Langfuse Cloud (PostgreSQL, ClickHouse, Redis, S3). Includes Docker Compose for development, Kubernetes Helm charts, and Terraform modules for AWS/Azure/GCP with unlimited traces and users.
Use Case:
Deploy enterprise observability for a financial services firm requiring complete data residency by self-hosting Langfuse on internal infrastructure while maintaining access to all prompt management, evaluation, and security features.
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$29.00/month
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$199.00/month
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ClickHouse acquired Langfuse in early 2026, bringing enhanced performance and enterprise support while maintaining open-source principles. Recent feature releases include Fast Preview (v4) performance improvements, inline comments anchored to specific text selections in traces (January 2026), tool call filtering with dedicated dashboard widgets (December 2025), and categorical LLM-as-judge scores for more nuanced evaluation. The pricing tiers feature (December 2025) enables accurate cost tracking for models with context-dependent rates like Claude Sonnet and Gemini Pro. Enterprise customers now have access to HIPAA BAA agreements and enhanced SCIM API capabilities.
Analytics & Monitoring
LangSmith lets you trace, analyze, and evaluate LLM applications and agents with deep observability into every model call, chain step, and tool invocation.
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Open-source LLM observability platform and API gateway that provides cost analytics, request logging, caching, and rate limiting through a simple proxy-based integration requiring only a base URL change.
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AI observability platform with Loop agent that automatically generates better prompts, scorers, and datasets from production data. Free tier available, Pro at $25/seat/month.
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Open-source LLM observability and evaluation platform built on OpenTelemetry. Self-host for free with comprehensive tracing, experimentation, and quality assessment for AI applications.
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