Monolith, a company that provides artificial intelligence (AI) software to engineering teams, announced its partnership with Cadillac Hertz Team JOTA. The team is leveraging the power of Monolith’s machine learning platform to enhance performance development for its pair of Hypercar challengers in the FIA World Endurance Championship, according to company officials in a press release.
In the new agreement, JOTA is implementing Monolith’s AI solution across a broad range of its motorsport activities, building on Monolith’s existing portfolio of customers in the motorsport sector. In the pursuit of highly efficient performance gains, Cadillac Hertz Team JOTA states that it is focusing its partnership with Monolith on data-driven car optimization, with Monolith’s AI platform set to time-efficiently refine the setup of the team’s hypercar.
Monolith’s Next Test Recommender (NTR) program is at the center of the partnership. The solution analyses engineers’ data inputs to automatically rank the most impactful tests and setups to run, working with the Monolith Test Plan Optimization (TPO) to deliver an optimized, highly efficient test program, officials said.
Cadillac Hertz Team JOTA engineering personnel combine the Monolith platform with their MATLAB analytics suite and existing workflows, creating what it says is a powerful approach for vehicle dynamics analysis and optimization.
“Our focus is always on extracting maximum performance from every aspect of the car,” said Tomoki Takahashi, technical director at Cadillac Hertz Team JOTA. “Monolith AI enables us to interrogate complex datasets with speed and precision. By integrating their AI tools into our workflow, we’re able to make smarter decisions faster—ultimately helping us try and stay competitive at the highest level of endurance racing.”
Using Software To Fine-Tune the Performance of Hypercars
JOTA engineers harnessed Monolith’s NTR and TPO solutions with their min/max optimization modules to transform their approach to vehicle dynamics. By visualizing and analyzing specific design parameters across different suspension-damping configurations, the team says that it identified performance sweet spots significantly faster than through traditional methods. This data-driven methodology has proven valuable on test rigs, enabling refinements that achieved notable reductions in tire contact patch load and improved pitch control during acceleration.
When applied across multiple vehicle characteristics while accounting for complex input/output relationships, these minor enhancements collectively deliver the decisive margins that translate into performance advantages in Hypercar competition, the team said.
“Monolith’s partnership with Cadillac Hertz Team JOTA represents an ongoing collaboration, in which our industry-leading machine-learning tool suite goes hand-in-hand with traditional engineering approaches to complex physics challenges,” said Sam Emeny-Smith, head of Automotive and Motorsport at Monolith. “In a category as competitive as the FIA World Endurance Championship’s Hypercar class, teams need access to cutting-edge solutions that will get them ahead of the curve. Drawing on the team’s world-class engineering expertise and the power of artificial intelligence, we’re excited to progress on this journey and unlock even more performance for the squad’s Hypercar challengers.”
Monolith’s Goal Is To Cut Development Time by Half
Monolith says that it is democratizing AI for engineering, aiming to cut engineers’ product development cycle in half by 2026. Its bespoke SaaS platform uses no-code, machine-learning software, giving domain experts the power to leverage existing, valuable testing datasets for their product development. The platform analyses and learns from this information to generate accurate, reliable predictions that enable engineering teams to reduce costly, time-intensive prototype testing programs.
Integrating highly effective innovations such as the Next Test Recommender tool and the industry’s first AI-powered Anomaly Detector functionality, Monolith says that it provides engineers with intelligent solutions to develop higher-quality products in half the time.