The Planetary EngineforAI Agents&Real-TimeEarth
What is TerraLab?
A Planetary Environment for AI Agents
TerraLab is building an interactive digital twin of Earth where AI agents will learn by reshaping their environment. We combine the visual fidelity of Google Earth with the dynamic interaction of NVIDIA Omniverse—but at planetary scale. Our vision is that AI agents won't just observe; they'll terraform, build, and adapt their world in real-time.
The Problem We're Solving
Current AI environments force a tradeoff: you get either realistic data or dynamic interaction, but never both at scale. Cesium shows beautiful real-world terrain, but it's static. Game engines let you build and modify worlds, but they're tiny compared to real geography. Simulation platforms give you physics, but not the complexity of actual Earth systems.
What Makes TerraLab Different
We're building the first platform where AI agents can train on a procedural digital twin of Earth that responds to their actions. An AI agent will be able to excavate terrain in the Sahara, and the physics engine will immediately update ground vehicle pathfinding. It can modify urban infrastructure in Tokyo, and traffic patterns will adapt in real-time. Everything will scale from global positioning to local interaction.
What AI Agents Will Do
- Terraform landscapes: Modify terrain and watch ecosystems and infrastructure adapt automatically
- Learn from consequences: Every action will create immediate feedback from realistic physics and environmental systems
- Scale contextually: Navigate from satellite-level strategy to street-level tactics seamlessly
Built for Global Scale
The core engine uses dynamic level-of-detail streaming to handle Earth-scale data efficiently. We solve floating-point precision issues that break most planetary simulations through dynamic origin shifting. The procedural generation system creates realistic terrain that responds to AI modifications instantly, backed by 15 years of optimization.
