Hugging Face

AssetOpsBench: Bridging the Gap Between AI Agent Benchmarks and Industrial Reality

AssetOpsBench is a new benchmark that evaluates agentic AI in industrial asset‑lifecycle management using 2.3 M sensor points, 140+ curated scenarios, 4.2 K work orders and 53 structured failure modes. It scores agents across six qualitative dimensions—task completion, retrieval accuracy, result verification, sequence correctness, clarity and hallucination rate—providing richer feedback than traditional single‑metric tests. Early community trials show that even top models like GPT‑4.1 achieve only 68‑72 points, far below the 85‑point threshold needed for deployment, especially when multi‑agent coordination is required. The framework also delivers automated failure‑mode analysis via a trajectory‑level pipeline, helping developers pinpoint why agents falter without exposing sensitive data.