Inspect

Inspect is a state-of-the-art open-source evaluation framework developed by the UK AI Safety Institute to standardize the measurement of large language model (LLM) capabilities and safety profiles. Built on a modular Python architecture, Inspect allows researchers and AI architects to define 'Tasks' comprising three core components: Solvers (the logic driving the model), Scorers (the metrics for success), and Datasets (the evaluation samples). Its technical architecture is specifically designed to handle complex, multi-turn agentic workflows where models must use tools, interact with sandboxed environments, and solve multi-step problems. By 2026, Inspect has transitioned from a government research tool to the industry standard for enterprise LLM validation, bridging the gap between raw model performance and production-ready safety requirements. It provides native support for virtually all major model providers, including OpenAI, Anthropic, Google, and local vLLM/Ollama deployments, ensuring a unified interface for cross-model benchmarking. The framework's ability to generate high-fidelity 'Inspect Logs' enables deep forensic analysis of model reasoning paths, which is critical for compliance with emerging global AI regulations like the EU AI Act.