Physical-world data
for embodied AI
in Latin America.
Motion Lab builds mobile data collection infrastructure to generate localized POV datasets for robotics, AI, and multimodal model companies.
Physical-world datasets we are building
Localized egocentric data from everyday Brazilian environments, designed for AI, robotics, and multimodal model development.
Washing Dishes
Multi-object manipulation including glassware, cutlery, and local ceramic textures under varying suds conditions.
Folding Clothes
Deformable object manipulation focusing on edge alignment and textile interaction physics in domestic settings.
Sweeping the Floor
Large-scale workspace interaction and reach-trajectory data across common Brazilian floor materials.
Geographic Diversity
Built to capture regional variation across Brazilian households, objects, lighting, surfaces, routines, and physical environments.
Neural Precision
POV video and structured metadata designed to support higher-quality training, evaluation, and validation workflows for physical AI.
Ethically Sourced
Collector participation is designed around consent, quality validation, task approval, and fair compensation for accepted missions.
Our Systematic Pipeline
From task design to validated physical-world datasets for AI and robotics teams.
Task Definition
Defining useful real-world interactions based on robotics needs and Latin American environmental context.
BR Network Record
Brazilian contributors receive guided missions through Trampo and record POV interactions with everyday objects and spaces.
Neural Audit
Quality checks review instruction adherence, visual clarity, safety, and dataset usefulness before approval.
Global Delivery
Approved data can be structured, labeled, and delivered to AI, robotics, and multimodal model companies.