Monolith AI

Engineering teams at the world's leading automotive, aerospace, and industrial companies face immense pressure to innovate faster while navigating increasingly complex product designs. The traditional product development lifecycle is often a bottleneck, characterized by time-consuming and expensive cycles of simulation, prototyping, and physical testing. This process generates terabytes of valuable data, from CAD and CAE simulations to physical test results, yet much of this data remains siloed and underutilized. Engineers, the domain experts, often lack the coding and data science skills to unlock the insights hidden within this data, leading to repeated tests, avoidable mistakes, and a slower time-to-market. This inefficiency not only inflates R&D budgets but also stifles the very innovation it's meant to foster.

Monolith AI was founded to solve this fundamental challenge by placing the power of artificial intelligence directly into the hands of engineers. Our customers use the Monolith platform, an intuitive, no-code software solution, to transform their existing engineering data into a predictive asset. By building self-learning models from their historical simulation and test data, engineers can accurately predict the performance of new designs without the need for endless physical prototypes. The platform is designed to understand the complex, physics-based data unique to engineering, allowing users to rapidly find the root cause of failures, optimize test plans to be up to 70% more efficient, and calibrate complex systems in minutes, not months. By empowering engineers to become AI experts in their own domain, we help our customers like BMW, Mercedes, and BAE Systems to develop higher quality products, dramatically reduce development costs, and accelerate their innovation cycles by up to 50%.