ChronoSpace AI – The First Geometry-Native Foundation Model

AI is blind to reality. We're giving it eyes.

Today's vision models are trained on flat 2D pixels. They struggle to understand depth, motion, and physics essential for mission-critical domains where fidelity and temporal accuracy are non-negotiable.

The answer is geometry.

ChronoSpace AI is building the first Geometry-Native Foundation Model (GFM), trained on real-world 4D data: how people, objects, and environments move and interact across time.

Our GFM enables us to reconstruct highly realistic, dynamic 4D scenes from sparse inputs with the fidelity required for mission-critical deployment.

This unlocks true spatial intelligence: AI that understands physics, maintains temporal consistency, and generalizes across domains.

Geometry-native data unlocks Spatial AI.

Applications

Mission-critical domains demand spatial intelligence

Robots train on 4D reconstructions of human workflows, using geometry-native content that captures affordances and motion patterns with physics built in. These reconstructions also serve as high-fidelity simulation environments, enabling validation before deployment and closing the sim-to-real gap.

Analysts transform drone footage into battlefield 4D reconstructions for situational awareness and threat analysis. CCTV becomes explorable geometry-native security environments, while immersive 4D scenes train personnel across missions, logistics, and equipment.

4D reconstructions create geometry-native digital twins of factory floors, warehouses, and construction sites. They enable optimization, safety checks, and automation that pixels or CAD can't deliver. High-fidelity scenes can be replayed to test layouts, validate automation, and improve safety before deployment.

Leadership

Our team combines proven track records. Paul Walborsky built AI.Reverie, a pioneer in synthetic data for computer vision, acquired by Meta in 2021. Srinath Sridhar, co-founder and CEO, is Professor of Computer Science at Brown University and head of the Interactive 3D Vision Lab. Our breakthroughs in geometry-native AI have been published at CVPR, NeurIPS, and SIGGRAPH — and now we're turning research into reality.