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Machine learning models trained on engineering CAD data — for generative design, defect detection, manufacturing prediction, or assistive design — need their training data prepped at industrial scale. CADSharp builds CAD-to-ML pipelines that parse STEP, B-Rep, Parasolid, and ACIS kernels; clean, segment, and label geometry; and feed enterprise CAD libraries into multi-modal neural-network training pipelines. The model is the easy part; the data prep is where most ML projects either ship or stall. Services offered:

CAD Data Engineering for AI/ML Pipelines from CADSharp

  • B-Rep kernel programming for STEP / Parasolid / ACIS / OpenCASCADE parsing, geometric data cleaning and validation, segmentation and labeling pipelines, attribute and metadata mapping, large-scale CAD library preparation for 3D neural networks, multi-modal dataset generation (geometry + drawings + metadata), MLOps and data-pipeline integration, and synthetic-data generation for training augmentation

  • Responsive technical support for your development team through Slack or email

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