For years, data scientists have struggled to integrate CAD data into their models, relying on manual scripts, complex workflows, and expensive dependencies. HOOPS AI offers a streamlined solution, integrating CAD access, dataset preparation, and encoding into a single, efficient framework. This promises to significantly accelerate the development of machine learning models in engineering.
CAD data, the lifeblood of modern engineering, has remained stubbornly resistant to AI integration. Existing methods are often clunky, slow, and prone to breaking. The constant evolution of research methods and design processes adds another layer of complexity, rendering previous efforts obsolete.
HOOPS AI seeks to dismantle these barriers by providing a unified environment for data scientists and machine learning engineers. It streamlines the process of preparing data, managing experiments, and building ML models, enabling teams to focus on innovation rather than data wrangling. The result, according to Tech Soft 3D, is a transparent and efficient workflow.
HOOPS AI builds upon the foundation of HOOPS Exchange, a CAD import/export library that provides direct access to over 30 file formats, including geometry, topology, assemblies, PMI, and metadata. This access is facilitated through a Python API, eliminating the need for intermediate file conversions and reducing reliance on third-party CAD systems.
This framework automates dataset preparation at scale, offering tools for visualization, segmentation, and cleaning. It also includes encoders that convert CAD models into ML-ready formats. HOOPS AI manages ingestion, versioning, and experiment tracking, ensuring reproducibility and providing clear insights at every stage.
Key Features of HOOPS AI
- Direct access to over 30 CAD file formats
- Automated dataset preparation with visualization, segmentation, and cleaning tools
- Encoders for converting CAD models into ML-ready formats
- Storage and logging utilities for traceability and experiment repeatability
HOOPS AI covers every stage of the machine learning lifecycle. Its storage and logging utilities capture the entire workflow, providing traceability and enabling repeatable experiments. This allows teams to iterate rapidly, leveraging a tool that works as fast as they do.
Tech Soft 3D brings decades of experience in CAD data access to this new framework, having processed vast amounts of data across multiple platforms. Their solutions are already used by industry giants such as Siemens, Hexagon, NVIDIA Omniverse, Unreal Engine and Unity 3D.
“With growing interest in applying machine learning to design, simulation, and manufacturing, more efficient integration of AI and CAD tools has become increasingly important.”
Whether it’s data scientists, startups, software vendors, or researchers, HOOPS AI aims to empower innovators to unlock the full potential of 3D data in their machine learning and AI applications. Further details can be found on the techsoft3d.com website.
The launch of HOOPS AI signifies a crucial step towards democratizing AI adoption in engineering. By lowering the barrier to entry and streamlining the workflow, Tech Soft 3D is paving the way for a future where machine learning and CAD data work hand-in-hand to drive innovation across industries.