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. Similar Parts Search is a technology demonstration that explores how combining Graph Neural Networks (GNNs) with advanced 3D geometric processing can significantly improve and streamline the discovery of structurally similar 3D parts within large engineering model repositories.

The MCP Connector for Autodesk Platform Services® and Procore® is a technology demonstration that leverages the emerging Model Context Protocol (MCP) standard and AI‑powered natural language processing to showcase how organizations can seamlessly bridge the gap between Building Information Modeling (BIM) and construction management. By integrating Autodesk Platform Services® (APS) for model visualization, geometry, and design metadata with Procore® for budgets, cost codes, and progress tracking, it enables users to query BIM models conversationally, extract element properties and quantities, and automatically synchronize results with Procore budget items and codes. The demonstration also contextualizes unstructured field data from Procore against BIM elements and visualizes real‑time construction status in color‑coded 3D, helping eliminate duplicate data entry, reduce inconsistencies, and maintain a unified source of truth—aligning design intent with field execution and laying groundwork for lifecycle interoperability.

AI Proposal Generator is a technology demonstration that explores how combining generative AI with retrieval-augmented generation (RAG) can improve and streamline proposal development. It shows an approach to managing high-volume, time-sensitive requests for proposals, accelerating turnaround time, ensuring brand and messaging consistency, customizing content for different project contexts, maintaining compliance, and automating routine tasks through context provisioning—drawing on previous project experience, company standards, and domain-specific nuances.