Langfuse: Promo Codes & Discount Coupons for April 2026

Overview

Langfuse captures end-to-end traces, inputs, outputs, and metadata from LLM applications to inspect failures and build labeled evaluation datasets. The open-source SDKs integrate with popular LLM and agent libraries and support self-hosted or managed deployments. Teams use it to monitor model behavior, track performance, and iterate on prompts and workflows.

Use cases

1. Debug unexpected model outputs and trace the source of failures.
2. Generate labeled evaluation datasets from real application traces.
3. Monitor production model performance and latency over time.
4. Compare behavior across model versions and prompt variants.

How it helps

• Reduce time to diagnose model errors by surfacing call-level traces and context.
• Improve model quality through reproducible evaluation datasets and label workflows.
• Increase operational efficiency with unified logs, metrics, and integrations.
• Support safer deployments by enabling visibility into tool calls and prompts.

• Capture detailed traces of model calls, I/O, and tool interactions for faster debugging.
• Aggregate metrics and exports for Data Analytics and performance tracking.
• Open-source SDKs with drop-in tracing for popular LLM and agent libraries.
• Versioned datasets and labeling tools to build eval sets and track drift.
• Self-host or use managed deployments to control data and scale operations.

Starts with a free plan for hobby use; no credit card required. Check the official site for current details.