AI Labs · Spatial intelligence

Training-grade data for spatial intelligence.

VLGE turns how worlds are built, played, and explored into synchronized 3D environments, telemetry, event streams and behavioral micro-signals: the human behavioral data layer for systems learning to operate in 3D.

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What a session looks like.

Every session people build and play becomes a continuous event feed of pose, velocity, state changes and dwell, time-aligned with source timestamps. Exports preserve the inferred source cadence and can be resampled to a buyer's training cadence. Below are four real captures, replayed and interleaved as they're stored.

The corpus

Every state, in one view.

Each point is one timestamped state — 61,736 across 30 sessions, a browser-sized sample of a much larger captured corpus. Enough to read the structure, synchronization and signal quality for yourself. Drag to orbit; hover any point to read its raw JSON.

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Process layer · decision-making

The moment of decision.

Where a person hesitated, weighed it, and committed to a direction — read straight from the deliberation, hesitation and movement channels of one real session. The cognitive layer no robotics or driving dataset captures.

Process layer · interaction

Not just where they go — what they do.

Movement is half the story. The other half is the build itself: every object a person places, and every time they move, rotate, scale or light it. Below is one real Edit-Mode session replayed from its event log — scrub the timeline, or switch builders. Each tick is a real recorded action.

Two people, one space,
two completely different paths.

Most datasets capture what a space is. VLGE captures how it's used: one person wanders and lingers while the next walks straight through. The same world produces opposite behavior, and every number here is read straight from the two real captures below.
behavioral ground tracks ● 2 sessions · real capture
session Asession B straightness dwell pauses ≥0.5s radius of gyration

What data is available

One session. Every data stream, aligned.

The console plays one real captured session end to end, with every panel reading the same playhead. As you scroll the streams, it re-reads that session through each one.

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3D Environments

Production-grade interactive 3D scenes, from interiors and streets to towers and stores, authored to be walked and played inside online.

watertight geometry · materials · navmesh · floor plans
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3DGS

Gaussian-splat captures of worlds built and recorded from reality: photoreal radiance fields for training perception and novel-view synthesis at the fidelity the physical world actually has, with derived perception labels for registered geometry.

splats · radiance fields · multi-view · intrinsics · depth · masks · 2D/3D boxes
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Spatial Metadata

The structured layer beneath the geometry: labelled zones, object semantics, adjacencies, sightlines and coordinates, the grammar a model needs to reason about a space. Buyer exports define metrics in fixed time windows so fingerprints compare cleanly across sessions.

coordinates · semantics · zones · sightlines · time-window metrics · fingerprint
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Continuous Event Streams

Timestamped behavior at inferred source cadence, with buyer-cadence resampled exports: pose, gaze, velocity, dwell, build and interaction events. This is the record that turns a static scene into how it's actually used, and it's the JSON streaming on the right.

pose · gaze · dwell · interactions · build-log · JSON · resampled exports
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Custom Data Collection & Delivery

Need a specific environment, task, population or modality? We build the world, run the collection, and deliver the dataset to your spec, ready to scrub, sample and export.

bespoke worlds · task instructions · audio/transcripts · co-present agents · scheduled delivery

Delivery package

Built for technical diligence, not just demos.

The live instruments prove synchronization. For qualified evaluations, VLGE packages the same streams into structured exports, enrichment layers and benchmark-ready splits through direct engagement.

01

Structured Export

Field-level mapping, coordinate frames, units, timestamps and video/telemetry alignment handled with the data team.

02

Behavioral Enrichment

Optional per-frame families for data quality, egocentric kinematics, action tokens, attention, spatial coverage, surprise and micro-signals.

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Perception Exports

For registered geometry: calibrated cameras, depth, semantic/instance masks and projected 2D/3D boxes.

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VLA Task Layer

Instruction prompts, task transcripts, audio and success/repair labels for vision-language-action training.

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Multi-Agent Capture

Synchronized co-present sessions for social navigation, collision avoidance and crowd-modeling studies.

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Benchmarks & Baselines

Reference splits and starter tasks for world models, embodied agents, robotics and simulation pipelines.

Example applications

Built for the systems learning to operate in 3D.

01
build logs · geometry

World Models

Ground generative world models in how real spaces are built and changed.

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human trajectories

Simulation

Populate simulators with real human trajectories, not scripted agents.

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timestamped pose · navmesh

Robotics

Navigation & manipulation priors from human behavior in 3D.

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9 behavioral channels

Embodied AI

Agents that learn to perceive, plan and act in physical space.

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benchmarks · fingerprints

Spatial Intelligence

Benchmarks & datasets for the research defining the field.

A growing library of spatial datasets for today's research, flexible for tomorrow's.

Request data access Talk to the data team →