Nuclearn, a leading provider of AI solutions purpose-built for the nuclear industry, announced the launch of Equipment AI, a new product that connects sensor data, work history, operator logs, condition reports, procedures, design documents, and maintenance guidance into a single AI-powered workflow. The product helps nuclear teams diagnose equipment issues and manage alarms in real time and with more confidence.

"Alarm fatigue and the loss of institutional knowledge as our most experienced engineers retire are two of the biggest risks facing this industry," said Brad Fox, CEO of Nuclearn. "Equipment AI addresses both at once - putting decades of plant experience in front of the engineer at the moment they need it. Leveraging AI to create a meaningful shift in how nuclear utilities approach plant reliability is why we started Nuclearn in the first place, and Equipment AI is a direct result of that mission."

Nuclear plants monitor thousands of components, and even a routine day can bring a steady stream of low level alarm notifications. Separating a nuisance alarm from a genuine equipment concern is a full-time job, yet the information needed to make that call, including sensor trends and the plant record behind them, typically lives across multiple disconnected systems. Most AI tools analyze either sensor data or maintenance records, but rarely both. Equipment AI reasons across time-series data and unstructured plant information in a single platform, producing a complete picture rather than an isolated chart, alarm, or work order. Beyond sharper diagnostics, it's also helping the industry preserve decades of engineering knowledge as it prepares for its next generation of workers.

Equipment AI brings together nuclear domain knowledge, utility data integrations, and source-grounded AI workflows, giving teams a purpose-built way to connect equipment data, plant documentation, and operational context in one place. It is built for the systems nuclear teams already use, including plant historian (PI) data, work order systems, and CAP/condition report platforms, and is designed with the security, traceability, and audit-trail requirements the industry expects.

"Most tools challenge teams to find and aggregate sensor trends supporting the paperwork, and the applied first principles engineering behind it. Equipment AI does both at once, giving engineers the full picture of what a piece of equipment has been telling them, not just a fragment of it," said Lorenzo Slay, Vice President of Product at Nuclearn. "This is especially true in nuclear power, where the context behind an alarm often lives in a work order, a condition report, or a procedure written years ago. Equipment AI brings all of that together in real time, so teams can make a faster, better-informed call."