The Data Infrastructure for the Era of Physical Intelligence
Roboloop is the infrastructure layer frontier robotics labs build on: egocentric capture, specialized human annotation, and AI-assisted quality control, delivered training-ready.
High-Quality Robotics Data Is Hard to Get
Bad labels cause robots to fail — like missing a grasp or colliding with obstacles. Building in-house labeling teams is expensive and doesn't scale.
Temporal Consistency
Sequential frames and point clouds must maintain labels across time — one missed frame breaks the whole sequence.
3D Spatial Understanding
Occlusions, depth perception, and multi-sensor fusion require specialized annotation skills most labelers don't have.
Safety-Critical Precision
In production robotics, annotation mistakes don't just hurt metrics — they cause collisions, drops, and failures.
A Unified Infrastructure for Robotics Data
Egocentric collection, robotics-specialized annotation, and AI-assisted quality control — one pipeline from raw capture to trained model.
Custom Workflows
3D bounding boxes, video sequences, LiDAR point clouds, grasp points, trajectories, and temporal tracking — all natively supported.
Robotics-Specialized Workforce
Trained labelers who understand manipulation, perception, and safety requirements, not generic crowdsourcing.
Train-Ready Delivery
Standard embodied-AI dataset formats with full provenance, so data drops straight into your training pipeline.
From Raw Data to Production-Ready Datasets
Upload
Multi-camera video, LiDAR point clouds, sensor streams
→Annotate
3D bounding boxes, object tracking, grasp points, trajectories
→Verify
Temporal consistency checks, multi-pass human QA, LLM-assisted validation
→Deliver
Training-ready datasets with confidence scores, metadata, and full provenance
Silicon Valley Quality, Asia Efficiency
Based in Singapore and built to tap Southeast Asia's technical talent pool, we're structured to deliver world-class results at a fraction of US/EU cost.
Cost Advantage
Southeast Asia's labor costs run well below US/EU rates, and we pass that structural advantage on to early partners.
Technical Talent
Singapore robotics research hub (NTU, NUS). Strong STEM talent pool with English proficiency for direct collaboration.
Built to Scale
Time zone coverage for faster turnaround, with a Singapore base and a workforce model designed to scale with demand.
Ready to Scale Your Robotics Data?
Let’s talk about your robotics data needs.