This platform converts vast urban data streams into actionable forecasts for mobility and energy demand, using a digital twin to anticipate city dynamics and guide proactive decisions, and it is designed for enterprises, researchers, and government bodies seeking proactive, data-driven solutions. Key features include real-time ingestion of mobility, energy, and weather data; machine learning at scale with transformer-based models and graph neural networks; interactive dashboards for traffic flows, energy forecasts, and what-if scenarios; an enterprise-grade, scalable architecture with solid data pipelines and modular components; and open-source, reproducible pipelines that invite collaboration, transparency, and community contributions, while addressing the gap between yesterday's numbers and today's disruptions by delivering foresight into grid surges and congestion so organizations can act with speed, accuracy, and confidence.
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