Data Ops
Human-driven capture
at dataset scale.
An in-house team of skilled operators playing thousands of hours of simulation and game content — generating authentic, action-conditioned behavioral data that procedural generation alone can't replicate.
Real behavior is the signal. Scripted behavior is noise.
World models need to learn how agents actually make decisions — not how a script says they should. The most valuable training data carries authentic human judgment: the hesitation before a turn, the path around an unexpected obstacle, the recovery from a mistake.
Our operators are skilled players who understand what diverse, high-signal gameplay looks like. We don't run bots. We run people, at scale, in structured sessions designed to maximize scenario coverage per hour.
Session design
We define the scenario matrix with your team — environment types, behavioral targets, edge case distributions, and hours required.
Scaled capture
Our operator team runs structured sessions across your simulation or game environment. We scale operator count rapidly to meet delivery timelines.
QA & annotation
Operators flag anomalies, annotate behavior states, and provide structured feedback as a natural part of the play session — no separate annotation pipeline required.
Storage & delivery
We handle all raw capture storage, post-processing, and structured delivery. Data arrives annotated and ready to train on.
What the Data Ops team delivers
High-volume capture
Structured operator sessions across simulation and game environments. We target maximum scenario diversity per hour — not just raw hours on a single environment.
- Scalable operator team — ramp up within days
- Structured session protocols for scenario coverage
- Multi-environment and multi-title capability
Data storage & delivery
We manage the full capture-to-delivery pipeline. Raw sessions are processed, filtered for quality, synchronized across all eight data layers, and packaged for direct ingestion.
- Secure, redundant raw session storage
- Automated quality filtering before packaging
- Delivery in researcher-specified formats
QA feedback
When an operator plays 10,000 hours in a simulation or game, they notice things no automated test finds. We can formalize this into structured QA reports — bug logs, edge case flags, physics anomalies, and behavioral inconsistencies — delivered alongside the capture data.
- Structured bug and anomaly reporting
- Edge case flagging and classification
- Environment fidelity and behavior feedback
Custom scenario coverage
If your training spec requires specific scenario types or behavioral distributions, our operators run targeted sessions designed to hit those exactly — rare events, edge cases, or adversarial interactions that procedural generation underproduces.
- Rare event and long-tail scenario targeting
- Adversarial and recovery behavior capture
- Multi-agent coordination scenarios
Built to deliver at dataset speed
Tell us your hours target and timeline.
We'll scope the operator team, session design, and delivery schedule — and come back with a plan that hits your dataset needs.