Simavai offers an AI-native platform called Forge AI that streamlines engineering simulations from model setup to interactive 3D visualization. By guiding users through physics definition, boundary‑condition configuration, and parameter selection, the platform cuts setup time by up to 85 % and accelerates the path from design concepts to actionable insights.
Funding
Funding not disclosed
Founders
Product
Problem
Engineering teams often spend extensive time manually configuring simulation models, selecting turbulence models, and setting boundary conditions, which delays design iteration and requires costly on‑premise HPC resources.
Solution
Simavai offers an AI‑native platform that guides users through the entire simulation workflow—from model setup to result visualization—using intelligent recommendations to auto‑configure physics and turbulence parameters. The platform runs simulations on scalable cloud compute, eliminating the need for local HPC clusters and delivering results faster. Real‑time 3D visualizations let engineers interact with flow fields and pressure contours, turning raw output into actionable insights without additional post‑processing tools. By automating setup and providing cloud‑based execution, Simavai reduces simulation preparation time by up to 85%, accelerating the transition from concept to design decision.
Target Audience
Primary users are mechanical, aerospace, and automotive engineers, as well as simulation specialists in product development teams that require rapid CFD and multiphysics analysis.
Features
- AI‑driven guided workflows that automatically select physics models, turbulence settings, and boundary conditions
- Cloud‑native compute engine that launches and manages simulation jobs without on‑premise HPC hardware
- Real‑time interactive 3D visualization of flow fields, pressure contours, and other results
- Automated workflow generation and parameter optimization to minimize manual setup effort
- Integrated AI Setup Assistant that continuously refines simulation configurations based on best practices