Secondmind provides a cloud-native optimization engine that utilizes Active Learning to enhance the design and calibration processes for automotive engineers. This technology reduces design simulation time and the number of iterations needed, enabling faster development of energy-efficient vehicles while minimizing reliance on costly prototypes.
Funding
$68M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Automotive engineers face increasing complexity in designing and calibrating software-defined vehicles, leading to lengthy design simulation times and reliance on costly physical prototypes. Optimizing energy efficiency and performance throughout the vehicle lifecycle requires extensive experimentation and data analysis.
Solution
Secondmind offers a cloud-native Optimization Engine powered by Active Learning to streamline the design and calibration processes for automotive engineering organizations. The engine reduces design simulation time and the number of iterations needed, enabling faster development of energy-efficient vehicles. It facilitates the creation of high-precision control strategies and calibration maps with fewer physical prototypes. The platform provides intelligent, automated experimentation, high-precision data-efficient modeling, blended intelligence, and explainable, transparent results.
Target Audience
The primary users are automotive engineers and engineering organizations involved in the design, development, and calibration of software-defined vehicles.
Features
- Cloud-native platform accessible at scale and secured
- Active Learning algorithms for efficient exploration of design choices
- High-precision modeling to reduce error correction costs
- Automated experimentation to optimize complex engineering systems
- Explainable AI for transparent and understandable results