IoT and robotics are unlocking smart, autonomous systems—from connected cities to automated factories—yet collecting real-world data is costly, slow, and often restricted by privacy and safety concerns. Dedomena.AI removes these barriers by generating high-fidelity synthetic datasets that preserve statistical integrity without exposing sensitive information.

Dedomena.AI’s end-to-end pipeline crafts realistic sensor logs and event streams, enriches existing telemetry, and streamlines model training. By blending physics-based simulation with procedural and generative methods, it delivers diverse, labeled data across vision, time-series, and structured formats—drastically cutting annotation time and speeding up AI development.

From predictive maintenance and smart-home behavior modeling to warehouse routing, drone simulations, and robotic swarms, Dedomena.AI powers 20 key applications. These use cases demonstrate how synthetic data drives robust AI for coordination, anomaly detection, digital twins, and compliance testing—enabling secure, scalable automation.