Langfusev0.1.2

Replace inline prompt literals in an LLM application with Langfuse's prompt management system. This enables centralized version control, deployment, and collaboration on prompts across teams.

Instrument an AI agent or chatbot with Langfuse tracing using SDKs or OpenTelemetry to capture detailed execution traces, latency, and cost metrics for debugging and performance optimization.

Create Langfuse datasets and attach scores to trace observations or dataset runs to automate quality checks and regression testing across model versions or prompt iterations.

Deploy Langfuse on internal infrastructure to meet data residency and security requirements, configuring environments, SDKs, and authentication for on-premise usage.

Use Langfuse public API or SDK namespaces (e.g., api.observations, api.metrics) to extract trace data, scores, and custom metrics for dashboards, alerts, or downstream analytics pipelines.

Offer a tiered subscription based on the number of traced LLM calls or active projects, targeting startups and enterprises that need observability without self-hosting.

Sell a self-hosted version of Langfuse with premium support and compliance certifications (SOC2, HIPAA) for industries with strict data governance requirements.

Provide managed integration services to embed Langfuse into existing AI workflows, including prompt migration, custom dashboarding, and evaluation pipeline setup.