World Model Infrastructure

World Model Data,
Captured at Street Level

We build high-fidelity, multi-perspective video datasets for training world models, autonomous systems, and embodied AI — sourced from real-world urban environments across the globe.

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The Challenge

World Models Need
Real-World Data

World models trained solely on synthetic data lack the complexity and chaos of real urban environments. RiderCam captures the missing signal — dense, multi-perspective, physically grounded video from streets worldwide.

🌐

Synthetic Alone Isn't Enough

Simulated environments miss the long-tail complexity of real-world physics, lighting, and human behavior that world models must learn.

📐

Existing Data Lacks Diversity

Most video datasets are limited to a single viewpoint. Training robust world models requires ego-centric, exo-centric, and multi-modal perspectives.

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Scale Demands Infrastructure

Capturing, structuring, and delivering research-grade video data at scale requires purpose-built capture pipelines and annotation systems.

Data Verticals

Five Perspectives on
the Physical World

Each data vertical captures a distinct viewpoint critical for training generalizable world models — from first-person urban navigation to synthetic ground truth.

Ego-Centric Ride
POV
Ego-Centric Ride
First-person POV from riders and cyclists navigating urban streets
Ego-Centric Drive
CAM
Ego-Centric Drive
Forward-facing dashcam capturing driving dynamics and road scenes
Exo-Centric Static
EXO
Exo-Centric Static
Fixed-position CCTV and surveillance capturing scene-level activity
Synthetic Environment
SYN
Synthetic Environment
Game-engine rendered scenes with pixel-perfect ground truth
Industrial Scene
IND
Industrial Scene
Construction and industrial site footage with heavy machinery
5
Data Verticals
10+
Cities Worldwide
2K–4K
Resolution
60fps
Capture Rate
Why RiderCam

Built for World Model
Training at Scale

We are not a research lab releasing a dataset. We are data infrastructure — a purpose-built pipeline for capturing, structuring, and delivering real-world video at the quality and scale world models demand.

01

Multi-Perspective Coverage

Ego-centric, exo-centric, and synthetic viewpoints unified in one platform. Train models that generalize across camera positions and motion dynamics.

02

Global Urban Capture

Real footage from cities across the US, Asia, and Europe. Dense urban environments with diverse traffic patterns, weather, and lighting conditions.

03

Research-Ready Format

Structured episodes with synchronized 2K video, IMU telemetry, ambient audio, and hierarchical annotations. Ready for model training out of the box.

Let's Build the World Model
Data Layer Together

Whether you're training autonomous systems, building simulations, or advancing embodied AI — we have the data.

Request Access stevenli@expressionai.org