World models are moving AI from describing the world to acting in it. Unlike generative models, world models cannot rely on the open internet for training data. We extract millions of multi-modal, action-conditioned trajectories from video games — safe and controlled environments where every interaction is captured — and deliver them as training-ready datasets for the next generation of AI: world models and embodied AI.
Temporally aligned video, telemetry inputs, and ground-truth 3D state — all synchronized and training-ready.
Three properties decide whether a dataset can train a frontier world model. We engineer for all three at once.
Petabytes of synchronized capture and billions of ticks of gameplay. The current largest public datasets contain tens of thousands of hours. We are building toward one million.
Hundreds of different titles, thousands of different maps, physical environments, lighting conditions, and edge-case scenarios. Reduce the risk of overfitting and train your model across different environments.
Zero-loss engine output under formal licensing agreements, not web scrapers. No hallucinations and no alignment drift — exact temporal alignment on every frame. Every frame is the same source of truth the game itself runs on.
A high-tick, physics-rich, multi-agent environment with millions of skilled players generating diverse, intent-driven trajectories every hour.
200+ structured properties extracted per frame. Every chip below is a real column in your dataset.
Framework-agreement customers can request additional AAA titles, custom property extraction, or live engine instrumentation for novel research environments.
Generic video corpora teach a model what scenes look like. Our data teaches a model what a world is: a coupled system of state, motion, intent, and consequence, frame by frame, provably aligned.
Straight from the engine, not inferred from pixels: exact per-object position, rotation, and velocity for every entity in the scene. No perception noise, no labeling error, no occlusion guesswork. Your model learns the true geometry of the world instead of a noisy reconstruction of it.
The next state depends on the action taken — and that link is the hardest thing to source. We record raw controller and keystroke inputs aligned to the exact frame and state they produced. We don't infer it. We record it and align it to each single frame.
Hundreds of ground-truth properties tick and multiple ticks per frame. Not just highlights — the full trajectory. A dataset of a consistent world evolving rather than isolated moments.
In 2025, we published a position paper discussing game-generated data as an untapped resource for advanced AI training, and we are thrilled by the interest it has received from the research community. A huge thank you to everyone who has shared feedback and ideas so far, and we continue to push the boundaries and research collaborations with academic partners.
Please reach out if you are interested in what we are building. We look forward to collaborating with researchers working on world models, physical AI, and self-supervised learning.
The paper explores how game-generated data can open up new possibilities for advancing AI training. In particular, we dived into the Joint-Embedding-Predictive-Architecture (JEPA), a state-of-the-art architecture for world model building, with a vision for achieving human-level intelligence.
We do not ship raw video clips. We ship a coherent dataset: time-aligned video, telemetry, structured game state, perfect action labels, and controlled environments — all generated by the engine itself, all immediately usable for training. Our team bridges deep expertise across both gaming and AI, and we curate the best dataset for your specific needs.
1080p multi-view game capture, every frame timestamped to engine ticks.
Full positional, velocity, orientation, and physics vectors for every entity per tick. Semantic context, events, HP, inventory, weapon state, score, camera pose, depth — over 200+ annotations per tick.
Every stream synchronized from tick to frame. Precise alignment treatment guarantees no drift.
Labeled controller, mouse, and keyboard inputs aligned to frames — recorded, not inferred.
Bespoke scenarios and gymnasiums built from commercial titles with rich physics.
Player intention and tasks, event annotations, human-annotated planning of goals and sub-goal achievements, causal relationships.
Delivered in Parquet, HDF5, and JSON-L by default. Custom export pipelines available for framework-agreement customers.
The same capture stack we ship to labs, miniaturized into the browser. Run an agent (you), generate frame-aligned ground-truth state, watch a JEPA-style world-model (style browser) learner predict the next frame in real time, and export the per-frame CSV.
A 60-second mini-game running on a live capture pipeline. Frame-aligned telemetry, ground-truth 3D state, and action labels stream into a JEPA-style world-model (style browser learner) preview as you play — then download the exact per-frame dataset as CSV.
For pricing inquiries and commercial contracts, send your request below and our team will be in touch.
We envision a world where next-generation AI, deeply grounded in reality and aligned with human values, improves life everywhere. The new AI paradigm transcends static pattern recognition and truly understands the dynamic mechanics of the world.
Our vision is to be the trusted data layer and intelligence backbone that powers this transition — enabling AI systems to operate safely, predictably, and intelligently within the complex real world.
Worldmodeldata is built by a team that sits at the exact intersection the problem demands. We bring together serial entrepreneurs who have built and scaled companies, executives from the game industry who know how these worlds are made and how to access them at scale, world model specialists and ML engineers who understand precisely what the next generation of AI needs to learn from, and senior voices from AI and technology regulation who ensure that data is sourced the right way.
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