AMC Bridge’s latest technology demonstration, Similar Parts Search, explores how combining artificial intelligence (AI) with advanced 3D geometric processing can address these challenges and improve the discovery, reuse, and evaluation of structurally similar parts across engineering workflows.

Engineering and manufacturing organizations continue to face challenges when managing large repositories of 3D models, including manual shape comparison, inconsistent similarity assessments, and the time‑consuming navigation of extensive part libraries. Traditional CAD search and manual similarity methods rely heavily on metadata, naming conventions, or subjective human judgment—approaches that do not scale and often produce inconsistent results. AMC Bridge’s latest technology demonstration, Similar Parts Search, explores how combining artificial intelligence (AI) with advanced 3D geometric processing can address these challenges and significantly improve the discovery, reuse, and evaluation of structurally similar parts across engineering workflows. By leveraging learned geometric representations of 3D models, the POC enables consistent, geometry‑aware similarity detection across large repositories, independent of how parts are named or categorized.

When the founders of AMC Bridge formed our company a quarter century ago, we wanted to help clients with digital transformation – but we realized that technical know-how alone wasn’t enough. We had to develop a deep understanding of our customers – their ambitions, their competition, their existential challenges. What we’ve learned from hundreds of clients while engineering their software ecosystems holds true across enterprises. To move decisively, modern organizations need a secure, open platform that connects data, automates high-value work, and gives stakeholders clear, current context for their next moves.