Get your models diverse, scalable behavior data, fast.Powered by 150K+ consented contributors across 600+ game worlds.
Robotics is stuck between pilot and production. Policies generalize only as far as the experience they were trained on, and in open-ended deployment, failures concentrate exactly where that experience runs out.
Games are dense with the situations deployments fail on: surprise, contact, pursuit and recovery. Millions of hours are played every day, so the experience your model needs already exists. We capture it at the source.
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Every session pairs observation with the action that produced the next frame. The same trajectories supervise dynamics models, policies and planners.
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Each alternative solves part of the problem. Shard World is designed to satisfy all of it.
Shard World
Gameplay is our first scalable source of experience. Real play, recorded in the wild: contributors play on their own hardware, in their own sessions, with no scripts, bots or lab setups.
Specify the behaviors your model is missing. We instrument the title, recruit matched contributors from a 150K+ network and deliver exclusively to you, without you standing up a collection operation of your own.
Contributors are screened against your specification: title proficiency, hardware, skill distribution and play style.
Every task ships with an approved collection protocol, so trajectories are gathered under controlled, reproducible conditions.
Sessions are cleaned, validated against your schema and delivered training-ready.
Gameplay is our first source of experience. We are building the infrastructure that turns deployment failures into targeted training experience: diagnosed, sourced, trained on and verified, with a human approving every update.
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Our mission is to build collaborative momentum between intelligent machines and humans.
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Tell us what your model is missing. We turn around a representative session bundle fast, then scale with you from proof of concept to production volume.
Request a sample
Tell us about your team and what your model is missing. We will follow up with a session bundle scoped to your spec.