THE METHODOLOGY
SCIENTIFIC DELIVERY.
We treat AI data infrastructure as an engineering discipline, not an experiment. Precision, scalability, and impact are built-in defaults.
CAPABILITIES
OUR SOLUTION.
Six interconnected data systems that together form the complete infrastructure for Physical AI training at scale.
Egocentric Video Capture
We capture high-fidelity, first-person video data from real-world environments such as homes, factories, labs, and beyond. This egocentric perspective is essential for training embodied AI systems that must understand the world from a human or robot point of view.
Multimodal Sensor Streams
Beyond video, our datasets include synchronized audio, inertial measurement data, depth maps, and environmental sensors. This rich, multimodal grounding is what separates functional AI from truly intelligent systems.
Hand-Object Interactions
Physical intelligence requires understanding how hands interact with objects. We specialize in fine-grained hand-object interaction recordings with precise keypoint tracking, force estimation, and object state annotations.
Structured Task Annotations
Raw data is noise. Our expert annotation teams apply hierarchical task-level labeling, from atomic actions to long-horizon goals, creating datasets with the semantic richness required for genuine machine understanding.
Petabyte-Scale Pipelines
Data collection is worthless without the infrastructure to process and deliver it. Our distributed pipelines handle petabyte-scale ingestion, processing, and quality control — built on battle-tested cloud architecture.
Secure Delivery Infrastructure
Research data is sensitive. Our secure, encrypted delivery infrastructure ensures your data is protected at rest and in transit, with granular access controls and full compliance with international data regulations.
THE PROCESS
AI-FIRST DELIVERY.
A structured, outcome-driven journey — from first call to measurable impact.
Discovery & Requirements
We start with an introductory call to understand your research context, define the objective, align on success metrics, and identify constraints (data, systems, compliance, timelines).
Architecture & Data Plan
A senior data architect is assigned to your engagement end-to-end; responsible for pipeline design, technical decisions, delivery quality, and long-term maintainability.
Capture & Collection
Our field teams deploy egocentric capture rigs across your target environments, collecting synchronized multi-modal data streams at the quality and scale your models demand.
Build & Integrate
Development begins with rapid, iterative implementation covering core workflows, system integrations, and production-grade foundations (security, reliability, observability) from day one.
QA, Testing & Delivery
We run structured QA and scenario testing, validate edge cases, and ensure the system is stable, monitored, and deployment-ready. Delivery plans include rollback and operational playbooks.
Release, Support & Measurement
Post-release, we provide production support and continuous improvement. We track agreed outcomes and provide transparent reporting on what's working and what needs adjustment.
APPLICATIONS
WHO USES OUR DATA.
Robotics Research
Training general-purpose robot manipulation policies
Wearable AI
Powering contextual AI for AR/VR and smart glasses
Autonomous Systems
Real-world scene understanding for autonomous agents
Embodied LLMs
Grounding language models in physical world understanding
GET STARTED
READY TO ACCESS OUR DATA INFRASTRUCTURE?
Talk to our founders to learn how TRON Labs data can accelerate your AI research.