Interactive AI Eval Dashboards with Data Studio

This article concludes a series on designing and visualizing AI evaluations, focusing on building interactive, codeless dashboards using Google Data Studio. The author demonstrates how to connect evaluation datasets—exported from Inspect AI—to create visual tools that allow non-technical stakeholders to analyze model performance. By utilizing dynamic filters for metrics like latency, accuracy, and cost, users can perform conditional analysis to isolate model capabilities from infrastructure noise. The guide provides a pre-configured template that maps multi-dimensional evaluation data into scatter plots, bubble charts, and pivot table heatmaps. These visualizations help identify trends such as skill uptake and survivorship bias, moving beyond basic terminal-based diagnostics. The author emphasizes that while these dashboards are excellent for exploratory analysis, scaling to larger sample sizes is essential to achieve statistical significance for production-ready benchmarks, ultimately providing a comprehensive end-to-end telemetry pipeline for AI developers.