Record synchronized, multimodal operations in real environments and establish a reliable source for data production.
Explore capture capabilities ↓Real-world data infrastructure for embodied AI
From one real taskto lasting robot capability.
DataGrids connects real tasks, industrial data, and field operations to build robot capability that keeps improving at work.
Explore our capabilitiesFrom data to deployment
One operating chain for lasting robot capability.
Real operations become reliable records, industrial datasets, and deployed robot capability. Each service advances the same task toward long-term field work.
Translate operating knowledge and task requirements into datasets ready for training and evaluation.
Explore dataset development ↓
Bring capability into the field, retain operating evidence, and feed hard cases into the next improvement cycle.
Explore deployment operations ↓Embodied Data Capture
Capture the full context of every real operation.
We combine robot-native, UMI, and EGO methods around a specific robot, task, and environment. Our capture software connects field execution, quality control, and data return.Capture infrastructure
Match the capture setup to the robot, task, and operating space.
Connect task standards, field execution, and data return in one workflow.
Keep production rhythm, quality standards, and delivery batches consistent.
Multiple dimensions. One timeline.
Visual context, spatial structure, and motion enter the same production record.
Industrial Dataset Development
Go deep into industry. Build data around how work happens.
We work with industry partners to define processes, materials, environments, and acceptance criteria, then build training and evaluation datasets inside real companies, factories, and workstations.Operators work around circuit boards, fixtures, and tightly controlled workstations.
Assembly · Inspection · Component handling
Packages move through automated routes with handoff, routing, and exception points.
Conveyor flow · Sorting · Palletizing
Open aisles, product displays, and changing inventory shape continuous in-store work.
Replenishment · Picking · Shelf inspection
Preparation and transfer run continuously across shared tools and work surfaces.
Ingredient handling · Prep · Cleaning
People, equipment, defined routes, and time-sensitive handoffs shape daily public service work.
Assistance · Delivery · Safe navigation
Tasks span irregular rooms, movable objects, and long sequences of small actions.
Floor care · Tidying · Object return
Workers operate between dense rows, fragile produce, and changing growth conditions.
Harvesting · Inspection · TransportIndustrial task datasets
A data asset should preserve how the task actually happened.
Task & Environment
Industry context, workstation conditions, material variation, task goals, and acceptance criteria define how the data can be used.
Industry · Company · Factory · Workstation · TaskMultimodal Record
First-person imagery, depth, pose, robot state, and task events share one timeline and retain the full action context.
RGB · Depth · Pose · StateProduction & Quality
Task standards, production batches, processing steps, issue review, and acceptance results create a clear evidence trail.
Production record · Quality validation · Version controlTraining & Evaluation
Delivery is organized around model capability and robot tasks, so the dataset directly supports training, evaluation, and field validation.
Training · Evaluation · Hard cases · Skill dataRobot Deployment & Operations
Keep robot capability growing in the real world.
We connect models, robots, and concrete tasks through adaptation, on-robot evaluation, and field operations, then return operating evidence to the next data cycle.
Align the model and robot
Connect training data, robot interfaces, motion capability, and operating versions around one task goal.
Evaluate and run on site
Measure completion quality, operating state, and safety boundaries inside the real task environment.
Return hard cases to production
Bring exceptions, failures, and long-tail tasks back into data production for the next training and deployment cycle.
Operate on siteRetain task evidenceUpdate the dataImprove capabilityDeploy again
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