Case Study: Stellantis optimizes data indexing and anonymization with Deepomatic

Stellantis - Customer Case Study

Stellantis, the international automotive manufacturer, worked with Deepomatic to improve data indexation and anonymization for its R&D efforts around autonomous driving. The company needed a way to organize large volumes of driving video and contextual images while also identifying sensitive data to support GDPR compliance.

Deepomatic provided a no-code deep learning platform that lets Stellantis train image-recognition models to detect driving scenarios such as tunnels, snow, and nearby vehicles, then anonymize data when needed. The solution automated much of the manual work, increased reliability, supported GDPR compliance, and integrated with Stellantis’ existing environments on private cloud or local servers.

Stellantis

Jean-Louis Sauvaget

Vehicle Functional Architecture Expert