01. Mission
Building large-scale physical intelligence datasets to connect AI with the real world.
03. Main Focus
Bellu.ai Diversity Engine
Bellu.ai builds its own algorithms and Diversification Engine to ensure comprehensive demographic representation and balanced data across all physical intelligence datasets. Our engine systematically analyzes, detects gaps, and balances factors to create truly representative training data that scales without degradation.
Predictive Gap Detection
AI-based real-time detection of improbable or underrepresented combinations.
Automated Collection Recommendations
Suggests tasks, environments, or users to record next.
Adaptive Weighting of Rare Combinations
Prioritizes critical or uncommon scenarios for faster model improvement.
Scalable Multi-Task Coverage
Ensures balanced diversity across multiple tasks simultaneously.
Real-Time Client Dashboards
Shows coverage progress, gaps, and predicted improvements for transparency.
Studio Data Limitations
Studio data fails to capture real-world complexity. Controlled environments lack the natural variability, failure modes, and occlusion scenarios that AI systems encounter in actual deployment.
- /Failure modes and edge cases
- /Occlusion handling in real-world scenarios
- /Natural variability beyond controlled environments
Why Most Data Collectors Collect Garbage
Most data collection efforts prioritize quantity over quality, leading to datasets filled with redundant, low-value, or mislabeled samples. Without proper curation, diversity engines, and quality control mechanisms, collectors amass volumes of garbage data that dilute model performance rather than enhance it.
- /Quantity over quality metrics drive collection strategies
- /Lack of systematic curation and quality filtering
- /Absence of diversity engines leads to redundant samples
- /Poor labeling and annotation quality
- /Missing ground-truth validation mechanisms
04. Contact
We partner with labs and frontier companies to supply critical physical AI intelligence datasets including egocentric data, telemetry, and sensory logs.
For inquiries, reach out directly to the founder.
santhosh@bellu.aiSUBJECT: PHYSICAL_AI_DATA_PROVISIONING