How to Optimize Your 3D Workflows With Advanced Geometry Modification and Visualization

NAVASTO's AI-driven solutions transform engineering workflows, accelerating development cycles, reducing costs, and empowering innovation. From real-time CFD predictions to streamlined design workflows, discover how advanced geometry modification and visualization can optimize your 3D workflows for enhanced productivity and efficiency.


How to Optimize Your 3D Workflows With Advanced Geometry Modification and Visualization

Imagine a world where engineering limits are constantly redefined, and innovation isn’t just a buzzword but a tangible reality. This is the field of expertise of NAVASTO, which specializes in utilizing artificial intelligence (AI) to push the boundaries of engineering. 

Imagine yourself evaluating your designs with AI-driven simulation in real time instead of waiting hours for new results and being able to optimize your product multiple times in a single day with unlimited low-cost simulation iterations.

We help engineering teams generate real-time results interactively, turn them into informed decisions, and thus accelerate development for enhanced productivity and efficiency by empowering the engineers instead of burdening them with more work. We are committed to empowering engineers to meet the increasing productivity and resource efficiency demand in the development process.

AI in Engineering: NAVASTO’s Approach for Geometry Modification and Visualization with the navDesign plugin

The pursuit of efficiency, precision, and speed is constantly evolving. Companies are adopting AI-driven integration to accelerate Computer-Aided Engineering (CAE) methods and improve product quality and process efficiency.

A great example showcasing the power of AI-driven methods is Computational Fluid Dynamics (CFD) simulations. In image 1, the prediction of an AI model and the result of an actual CFD simulation are compared, showcasing the power of AI-driven methods in engineering. It is essential to say that the AI model was trained with only 100 samples and that the geometry in the case shown was unseen by the AI model. If you’d like to learn more about this collaborative work with our partner, FRIENDSHIP SYSTEMS AG, you can read about it  in this LinkedIn Post.