Never give up on your dreams.
What if you could finally perceive what others miss?
Stern Tech turns that ambition into technology: a French, proprietary, next-generation behavioral AI designed to analyze weak signals and reveal a new depth of analysis in demanding professional environments.
Five verticals. One breakthrough.
One behavioral intelligence technology, adapted for recruitment, market research, wellbeing, prevention, simulator-based training and interactive AI experiences.
Secure your recruitment process
An AI-enhanced professional assessment designed to better understand motivation, behavioral traits and role fit.
Discover Alex →
Reveal market insights
Analyze reactions, preferences and engagement signals from voluntary panels to support marketing decisions.
Discover Pegasus →
Identify sensitive signals
Advanced indicators designed to support the observation of psychological and social wellbeing needs.
Discover Shield →
Train better and drive smarter
A simulation-based training support solution with attention, vigilance and progress indicators.
Discover WiseDriver →Awaken a synthetic presence
A narrative and interactive AI experience exploring synthetic consciousness and a unique digital companion relationship.
Discover AnnaO →Built with leading ecosystems
Stern Tech is supported by innovation, research, technology and entrepreneurial ecosystems that help us build reliable, sovereign and human-centered behavioral AI.
These ecosystems reflect Stern Tech’s positioning at the intersection of deeptech, research, entrepreneurship, responsible innovation and sovereign AI.
Reliable, ethical and sovereign behavioral AI
Stern Tech develops behavioral AI technologies that are tested, documented and built through a scientific approach, designed to support human decision-making.
Our technology is fully designed, developed and owned in France. Human supervision is embedded by design, and our solutions are developed to support GDPR and AI Act compliant deployments.
Data processing is designed to preserve confidentiality, optimize energy use and run primarily locally on users’ devices.
No automated or autonomous final decision is made.
