Braintrust x Label Studio: debug and evaluate AI agents with observability traces

Overview
Braintrust is an AI observability and evaluation platform that helps teams trace, test, and improve AI applications. It helps teams trace prompts, responses, and tool calls, run systematic evaluations against real datasets, and monitor quality over time. By integrating Braintrust with Label Studio, teams can bring human-in-the-loop review into their evaluation workflows, enabling structured annotation of traces, outputs, and failure cases for better benchmarks and more reliable AI systems.

Benefits

• Improved observability: Trace prompts, responses, and tool calls to understand failures and quality issues in production.
• Human-in-the-loop evaluation: Use Label Studio to review and annotate Braintrust traces and model outputs for quality and correctness
• Better benchmark creation: Turn experiments, logs, and feedback into structured datasets for testing and regression analysis.
• Faster iteration: Combine Braintrust evals with annotation feedback to refine prompts, models, and agent workflows.
• Higher reliability: Build more robust AI products with continuous monitoring, scoring, and human review.