The Synthetic Infrastructure for AI

Physics-Informed AI for the Physical World

Eliminate data scarcity with 100% physically accurate datasets. Our engine automates high-fidelity training for complex environments.

New Agrotech Product​

We use remote sensing data from satellite together with physics simulations to help farmers manage their crops.

Industry Solutions​

Scale your AI training across high-complexity verticals using our physics-informed engine. We move beyond simulation to production-ready deployments.​

Agrotech

Robotics

Biotech

Our Partners​

We collaborate with different research and industry leaders.​

Correct and most promising solution!”​

This innovation is a critical unmet need, not only for our network of textile manufacturers but also for the robotics integrators and automation partners, who are actively developing the next generation of automated sewing and handling cells.

CITEVE

The Science Behind the Moat​​

Built by Physics PhDs, Engineered for Scalable AI Reliability.​

Zita Esteves, PhD

CEO (Physics, Management, and Dissemination)

Cristóvão Dias, PhD

CTO (Physics and Data Science)

Helder Esteves, MSc

PhD Student (Physics and Data Science)

Afonso Gorjão, MSc

Data Scientist (Physics and Data Science)

Tomás Almeida, Bsc

Master Student (Physics and Data Science)

Ready to scale your AI training?​

The use of physics-based synthetic data can make your AI model more than 95% reliable.