The Monolith team was able to identify faulty assumptions, unnecessary test conditions, and errors in our data using the Test Plan Optimisation Module. With their help, we’ve been able to reduce the number of tests in our plan by more than 70%.
-Director of Test, Major European OEM
How it works
Next Test Recommender
Guide your testing strategy with AI to define a better plan.
Start with a small set of test results or preload your current plan to generate progressive recommendations using AI.
Apply thousands of AI algorithms
Our recommenders apply thousands of algorithms to explore your design space and find the best model.
Generate test recommendations
With each iteration, AI recommenders find test conditions that explore your design most efficiently.
Test with confidence
By optimising your testing plan with Monolith you can reduce the number of tests by up to 70%, and proceed with confidence.
Developing efficient and effective test plans without jeopardising safety and reliability is the top barrier to bringing EV battery solutions to market.
-2024 Forrester Survey of EV Battery Engineering Leaders
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