A smart tool that reduces diagnostic time and guides users through efficient aftermarket repair workflows.
I led design on this 0→1 project, partnering with product managers and engineers to solve a critical pain point in industrial repair workflows. Through iterative design informed by ongoing customer feedback, we delivered an AI-powered tool that significantly reduced diagnostic time—helping secure a multi-year, multi-million-dollar customer contract.
The goal of this project was to reduce the time test engineers spent troubleshooting faulty equipment. I partnered with data scientists and product to surface predictive part failures and embed relevant maintenance manuals into the workflow. I designed a flow where users could easily validate recommendations and access the most relevant documentation in a single view. This approach reduced average repair time from 35 days to 12. The project demonstrated how design and AI could meaningfully reduce operational delays in critical infrastructure.
