datai.

Human activity.
Structured for
physical AI.

Find the physical tasks your research needs. Explore original footage, task context and timed actions by activity, then check the live catalogue for availability.

Hands repotting a plant at a garden workbench
REAL TASKS. USEFUL CONTEXT.

A package you
can inspect.

The recording, its labels and the evidence behind them remain distinct. Check each collection’s specifications before choosing it.

01

Original video

MP4 or WebM recordings of complete physical tasks. Source files stay private; licensed download access depends on the order’s confirmed payment and status.

02

Structured context

JSONL metadata and a CSV index connect recording references, activity, viewpoint and technical fields. Explicit provenance distinguishes measured properties from contributor declarations.

03

Timed actions

Action intervals describe visible steps on the recording timeline. Automatically accepted footage also includes a full analysis JSON with the model, processing versions and limitations.

Accounts and private uploads are open. New automatic analysis is waiting for its production connection. Paid checkout and contributor payouts will open later.

One activity.
Two ways to
build a selection.

Both selection types use the same approved inventory and preserve the recordings and annotations chosen for an order.

01 / CATEGORY BATCH

Bring contributors together.

Select a shared activity, such as gardening. The batch combines eligible recordings from several contributors; each allocation is based on the duration included from that contributor.

02 / CONTRIBUTOR COLLECTION

Choose a particular collection.

Explore one contributor’s activity offer and its recording specifications. A contributor may publish separate collections for different occupations, settings or tasks.

Catalogue filters help you explore collections. They do not cut clips or change an order’s frozen selection. Review its final summary before proceeding.

Choose the
physical task.

Twelve activity areas share one catalogue taxonomy. These guides describe capture and annotation choices; the marketplace reports current supply.

Start with
the task.
Make the brief concrete.

Describe what you want a model to observe, the variation you need and the evidence required to evaluate it. Availability and any additional capture or annotation work must be agreed for that request.

  • Visible task steps, initial state and intended outcome
  • Target hours, camera views, resolution and frame rate
  • Objects, tools, environments and evaluation exclusions
  • Action vocabulary, annotation layers and delivery format

Human video can support action understanding and learning from demonstrations. Ordinary footage does not supply measured robot commands, calibrated pose, depth, masks or force. Specialist labels need a separate specification and suitable capture.

Write a dataset brief

Explore the task.
Check the collection.

Open the marketplace