Synthetic RL envs
High-fidelity RL environments that simulate real business contexts — social platforms, job boards, markets and research — grounded in private company data.
Explore the worldsWorld models are fit to private company data, so simulated people and markets act the way real ones do.
Behavioral, auction and market dynamics with real incentives — not scripted bots or static datasets.
Change the population, the incentives or the market, then re-run the world and train again.
Each world is a set of calibrated models of the people and systems inside a business, composed into an environment your agents can act in.
Behavioral and auction models of X, Meta, LinkedIn and Telegram: how people post, follow and engage, and how ad inventory gets priced.
Behavioral models of recruiters and candidates: who searches, who reaches out, who replies, and who ends up hired.
Market models with simulated arbitrageurs, retail flow and competing strategies, so trading agents face realistic counterparties.
Environments for agents that do research: propose ideas, run experiments, read the results and decide what to try next.
We fit behavioral, auction and market models to a company’s private data, so every simulated actor responds the way its real counterpart would.
Users, recruiters, candidates, traders and competitors interact inside one world, at the scale and speed that training needs.
Your agents act, collect rewards and get evaluated against realistic counterparties before they touch production.
We work with teams training and evaluating agents that have to deal with real people and real markets. Tell us which context you want simulated and what data sits behind it.