Multimodal data infrastructure

Illuminate what models
can’t yet see.

High-quality image, video, interleaved, 3D, and visual reasoning data for frontier multimodal systems.

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The essential layer

The physical world is still largely dark to machines.

We build the visual data that makes it legible—carefully sourced, deeply structured, and evaluated against the capability it is meant to unlock.

A shared world

Many ways to learn it.

One scene becomes a family of complementary training signals, aligned at the source and built to work together.

IMG_0249.RAW✓ RIGHTS VERIFIED
Curated image corpora

Composition, objects, environments, and the long tail of the visual world.

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00:04
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Temporal continuity

Motion, cause and effect, action, camera behavior, and change through time.

What changed between the first and third frame?
RESPONSEThe light source moved behind the subject, changing the edge illumination and shadow direction.
Interleaved context

Visuals and language arranged in the sequences models encounter in real work.

OBSERVEreflections
COMPARElight direction
INFERcamera moved
Visual reasoning traces

Grounded steps that connect evidence, judgment, and a verifiable conclusion.

RGB-D / MULTIVIEW / NORMALS
Spatial understanding

Aligned views, geometry, depth, and material signals for three-dimensional intelligence.

Products

Data for the next capability.

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01

OTS Image Data

Rights-cleared, quality-ranked visual corpora with useful long-tail coverage.

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02

OTS Video Data

High-signal sequences for temporal understanding, world dynamics, and generation.

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03
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Paired Editing Data

Instruction, input, and verified output pairs spanning precise visual transformations.

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04

3D Data

Multiview, RGB-D, point cloud, and material data aligned for spatial learning.

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05

Design Data

Structured layouts, assets, critiques, and implementation pairs for visual craft.

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06

Custom Evals

Task-faithful benchmarks that expose the gap and measure meaningful model lift.

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Quality, made visible

Every datapoint should earn its place.

Volume is easy to count. Signal takes judgment. Our quality system is designed around the capability the data needs to teach.

  1. 01

    Source

    Start with provenance, permission, and the right distribution.

  2. 02

    Curate

    Shape the long tail around real model failure modes.

  3. 03

    Verify

    Combine programmatic checks with calibrated human judgment.

  4. 04

    Evaluate

    Measure whether the data moves the intended capability.

Custom programs

Tell us where the model goes dark.

We’ll design the data, collection system, and evaluation around the capability gap.

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