NuclearN, a leading provider of AI solutions for the energy sector, announced its partnership with DataGlance, the nuclear industry’s leading mobile digital work solutions provider. Together, they are developing an AI-driven work order planning solution to streamline the creation of step-by-step work instructions for corrective maintenance tasks to further enhance operational efficiency.
The new solution will combine NuclearN’s generative AI and DataGlance’s configurable workflows to automate key aspects of the corrective maintenance work order development process. Work order planning time will be reduced through AI-performed historic work analysis that then drives generative task creation, task-time determination, labor type assignments, parts and materials identification, and relevant operating experience selection. These automatons are projected to eliminate hours of planning and review time per work order generated.
“We believe AI can transform work order creation by automating repetitive tasks, freeing up valuable time for planners,” said Bradley Fox, CEO and Co-Founder of NuclearN. “Our AI, paired with DataGlance’s work order environment, will allow us to deliver a faster and more efficient solution,” said Jerrold Vincent, CFO and Co-Founder of NuclearN.
DataGlance brings over a decade of mobile digital work management experience while NuclearN delivers AI solutions that drive automation. This partnership aims to create an AI-powered work order planning tool that improves both process efficiency and accuracy.
“Our new work order planning solution represents a transformational step forward in electronic work package creation and execution,” said Nathan Ives, EVP of Business Development at DataGlance. “Using NuclearN’s generative AI technology, our solution enables the timely, accurate use of expert knowledge captured within the work orders, procedures, engineering documents, and regulatory licenses amassed during the decades of a facility’s operation.”
The NuclearN – DataGlance AI-driven work planning solution improves operational productivity and accuracy in asset-intensive industries reliant on detailed work planning and execution. It will automate tasks requiring significant time, making work order generation more efficient.
