World Intelligence
World Intelligence provides synchronized first-person sensor data streams—including 2D RGB video, depth maps, IMU signals, and spatial audio—with sub-millisecond temporal alignment. The company augments these raw streams with fully labeled, long-horizon trajectory data covering motion states, pose changes, action segments, and spatial context, delivering pipeline-ready, versioned datasets for teams building physical AI systems.
- Artificial Intelligence
- Robotics
Funding
Founders
Founder details are not available yet.
Product
Problem
Physical AI systems—including robotics, autonomous vehicles, and embodied agents—require a grounded understanding of the real world learned from real experience, not simulation. However, model development is increasingly limited by the availability of high-quality, well-structured real-world data rather than by model architectures or compute capacity.
Solution
World Intelligence supplies synchronized, first-person sensor data streams that capture real-world experience across multiple modalities, including 2D RGB video, depth maps, IMU signals, and spatial audio, all with sub-millisecond temporal alignment. Beyond raw data, the company provides structured, fully labeled trajectory data that enriches long-horizon sequences with motion states, pose changes, action segments, and spatial context, turning sensor streams into model-ready training data. This labeling layer transforms raw sensory input into usable intelligence for AI teams. All datasets are delivered in pipeline-ready formats with documented schemas and versioned releases, enabling teams to integrate them directly into their training workflows.
Target Audience
Primary customers are engineering and research teams building physical AI systems, including robotics companies, autonomous vehicle developers, and embodied AI research groups that need real-world, multi-modal training data.
Features
- Sub-millisecond synchronization across all sensor modalities, including 2D RGB video, depth maps, IMU signals, and spatial audio
- Long-horizon trajectory data enriched with motion states, pose changes, action segments, and spatial context
- Fully labeled structured supervision that converts raw sensor streams into model-ready training data
- Pipeline-ready dataset formats with documented schemas and versioned releases for reproducible AI development