AI Physics

AI Physics is a comprehensive digital engineering platform designed to transform engineering workflows by integrating compute, data, and AI. It accelerates modeling and simulation processes at an enterprise scale, offering capabilities from synthetic data generation to rapid solver predictions. The platform enables the deployment of AI-enhanced methods that significantly speed up and improve the accuracy of simulations, allowing for the exploration of a wide range of innovation possibilities.

The platform provides a complete AI stack for custom model development, enabling engineers to build production-ready AI models without requiring deep AI expertise. This end-to-end framework manages data generation, structuring, dataset creation, model training, evaluation, deployment, and inference services, transforming simulation data into powerful AI models through automated workflows that ensure traceability and version control.

AI Physics accelerates results with real-time simulation predictions, allowing users to explore large design spaces quickly. The AI inference models deliver results in seconds, maintaining accuracy comparable to traditional methods while facilitating rapid iteration and optimization. The platform integrates seamlessly with existing engineering workflows, providing instant feedback on design changes and parameter variations.

The platform includes a comprehensive library of AI models and applications, offering both custom and pre-built third-party AI model architectures optimized for engineering applications. Users can deploy validated models for common use cases or customize existing models to meet specific requirements, thereby accelerating project timelines by leveraging proven AI solutions.

AI Physics also enhances engineering data intelligence by analyzing vast amounts of simulation data to uncover hidden insights. Features like natural language search, intelligent summaries of job results, and pattern recognition help surface insights that might be missed by human experts. Smart tagging organizes simulations by context, and AI-driven job summaries transform technical results into easy-to-read visuals and reports, aiding in decision-making processes.

Organizations using AI Physics have reported significant improvements, such as 1000X faster design evaluations, 99% accuracy compared to traditional simulations, and an 85% improvement in computing resource efficiency. The platform supports various industries, including automotive, biomedical, and consumer goods, by enhancing solutions for CAE and AI/ML, delivering faster time-to-market, more efficient supply chains, and reduced R&D costs.