
Deformable-Object Manipulation
- Deformable objects
- Bimanual coordination
- Changing geometry
EGXO
Custom egocentric data programs for robotics, VLA systems, world models, and physical AI.

Define the tasks, environments, capture configuration, metadata, and quality thresholds your model needs. EGXO turns that specification into reviewable real-world data.
Choose the viewpoint from the model objective. Add synchronization only when correspondence earns the extra complexity.
Collection design follows the learning problem, required supervision, and the environment where the system must work.
Bimanual coordination, contact, tools, deformable objects, and recovery.
Visual sequences aligned with task language, steps, intent, and outcomes.
Long-horizon state transitions across natural environments and interruptions.
Whole-body activity, motion, geometry, obstacles, and multi-agent context.
Controlled variations, negative examples, failure categories, and robustness.
The same acceptance criteria should survive every handoff.
Model objective, tasks, views, environments, modalities, rights, and success.
Prove visibility, instructions, QA, privacy, and ingest before scale.
Run a versioned protocol with traceable task and session context.
Check media, metadata, labels, visibility, privacy, and acceptance.
Document releases and test them in the target data loader.
Crawlable proof
Six approved first-person previews show bimanual assembly, cleaning, deformable objects, packing, sorting, and tool use. Technical sanitization and public marketing review are complete.
Explore Sample Data
Bimanual alignment and folding of flexible material with continuously changing geometry—a frontier challenge for general-purpose robots.
Quality and governance
Capture protocol, media integrity, task visibility, annotation, privacy, consent, licensing, provenance, versioning, and buyer ingest are connected parts of one release.
Review the Control Framework ↗A buyer’s guide to first-person, third-person, and synchronized capture for robotics and physical AI.
Read Guide ↗How first-person demonstrations can support manipulation, VLA systems, navigation, and long-horizon task learning.
Read Guide ↗A procurement framework for deciding when public benchmarks are enough and when custom collection is justified.
Read Guide ↗Enterprise project brief
Share the task, environment, perspective, modalities, scale, format, licensing needs, timeline, and acceptance criteria.
Scope a Collection