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Langfuse: artificial intelligence features and setup
An open-source platform for observing, tracing, and evaluating AI agents and language models.
Tool by the Otomatzia editorial team · source content checked on
Overview
Langfuse is useful when a team runs agents or model calls and needs to see what actually happened during each run. It records traces, lets you compare prompt versions, and helps assess whether a change improved or worsened an outcome. You can connect monitoring to an existing process without replacing the automation layer. Before wider use, decide which fields to store, how long to retain history, and how to hide customer data in inputs and outputs.
Features
- Tracing agent runs and model calls
- Evaluations and comparisons between prompt versions
- Integration with existing code and automation processes
Business uses
- Investigating why a service agent gave a customer the wrong answer
- Comparing a new prompt version with an earlier version before release
Getting started
- Connect a test environment and send a few runs with non-identifying data.
- Define which fields are stored and which data is masked.
- Check a successful run, a failed run, and a small prompt change.
What to check
- Check what is actually stored in logs before connecting systems with customer data.
- Assign responsibility for evaluations so a prompt change does not reach production without review.
Sources to check next
Vendor features and prices change. Confirm details on the linked official pages before you rely on them.