Franco-German Partnership for Data Sovereignty in Defence AI.
We’re proud to announce a partnership between AI Verse and STARK.
AI Verse, a French deep tech company and European leader in synthetic data generation for training artificial intelligence models, announces a strategic partnership with STARK, a German defence company that develops multi-domain unmanned systems.
This collaboration aims to provide STARK with sovereign synthetic image datasets to train the onboard AI systems deployed on their platforms. The goal is to strengthen European autonomy in AI training data, a key challenge for the continent’s technological sovereignty and security.
By combining AI Verse’s expertise in controlled data generation with STARK’s excellence in unmanned systems across multiple domains, this partnership exemplifies Franco-German cooperation in deploying trustworthy AI, independent from extra-European sources.
More Content
8 Ways Computer Vision will Shape Defense in 2026 and Beyond
Computer vision and synthetic data are reshaping how defense organizations see, understand, and act in complex environments. These technologies are moving from supportive tools to essential layers in modern defense infrastructure. Here’s where their impact is already being felt—and what’s next. 1. Situational Awareness Gets Smarter Defense systems now merge live visuals from drones, vehicles, […]
Smart City Expo World Congress – Innovating Urban Security
The Smart City Expo World Congress 2024 (November 5-7) is a global platform for exploring cutting-edge urban security and smart city solutions. Attendees will discover the latest advancements and innovations in urban living. Visit Our Booth:Find us at Hall P3, Level 0, Street S, Stand 40 to discuss how our team contributes to smart city […]
How We Leveraged Synthetic Images to Train a Fall Detection Model
In the development of a computer vision fall detection model, one of the biggest challenges is obtaining high-quality, well-annotated image datasets. Real-world fall datasets are scarce due to privacy concerns, ethical constraints, and the difficulty of capturing diverse fall scenarios in real life. We tackled this challenge by leveraging synthetic images to train a highly […]