Neurocat's aidkit ensures the safety and robustness of AI systems, particularly in automotive and mobility applications. It identifies vulnerabilities and data gaps in machine learning models used for perception functions in ADAS and ADS systems, helping companies mitigate risks across operational design domain scenarios. The tool generates artifacts for model retraining, combines existing ODD attributes to discover new safe and unsafe areas, and integrates into MLOps workflows. It employs augmented data techniques for testing and supports scalable, customizable data augmentation processes to improve model reliability and compliance with safety standards.
