The DreamVu Pipeline

We customize the pipeline for every data challenge.

Each stage uses the best method available — open source where open source is better, our own where it is not. We publish in this field, so we track what changes, and we swap components when something better comes out. You tell us what your model needs to learn, and we build the pipeline for it.

Stage 01

Capture

Exocentric
Alia, our own camera. A single-shot 360° stereo panorama with depth, from one camera position.
Egocentric
A head-mounted camera on the worker, synchronized to the Alia stream frame for frame. Some datasets, such as navigation, use the ego camera on its own.
Wrist
An optional third camera for close manipulation and grasp detail.
Other cameras
If a program needs cameras other than ours, we use those too. The pipeline does not depend on any one camera.
Environments
Working venues. We have access to hundreds of venues across a range of industry segments.
Stage 02

Annotate

Method
AI does the first pass. A person reviews every batch. Segmentation, tracking, action boundaries, and task breakdown are set per program.
Components
The best current model for each task, replaced as the field moves. Our own components where published methods are not good enough.
Stage 03

Deliver

OutputCaptureUsed for
Manipulation datasetsEgo + exo + wristManipulation and action policy training
VLM datasetsEgo + exoVision-language model fine-tuning
Navigation datasetsEgo onlyNavigation and traversal policy training
World model dataAlia 16KGenerative video and world model training
Simulation environmentsAlia captureAny USD-compatible simulator — in development
3D objectsScanned separatelyAny USD-compatible simulator
Standards
OpenUSD. LeRobot (RLDS). Open X-Embodiment. VLM, navigation, and panorama deliveries have no single standard, so we agree the schema with you before capture starts.
If you need something that is not on this list

Tell us and we will scope it. We also run USD conversion with physics and domain-randomized rendering.

Quality

Four gates

Every capture passes four gates before we deliver it.

G1  Calibration
Checked for every rig, every session.
G2  Alignment
All camera streams confirmed in sync before annotation starts.
G3  Annotation review
A person reviews every batch.
G4  Rejection
Batches that fall below the threshold are captured again.

Full numeric specification available under NDA

Tell us what your model needs to learn.

Capture programs, research collaboration, and dataset partnerships.

Talk to us