Environments that mirror how work actually happens, with domain experts generating trajectories, preferences and verifiable rewards inside them. Agentic models learn the job, not the benchmark.
Real workflows from operating businesses, turned into environments a model can act in.
E-commerce operations, customer support, logistics dispatch and manufacturing SOPs rebuilt as interactive environments with the real tools, data shapes and edge cases.
Operators, support leads and planners generate demonstrations, preference pairs and rubrics inside the environment. Bilingual English and Chinese expert pools.
Where the business has a ground-truth outcome, such as a resolved ticket or a correct listing, the environment scores it. Where it does not, expert rubrics do.
Starting with the workflows we have run ourselves for years.
| Deliverables | Environment code and fixtures, expert trajectories, preference pairs, rubrics, reward functions |
|---|---|
| Volume | Pilot from 500 trajectories; production runs in the tens of thousands |
| Formats | OpenAI-style message logs, tool-call traces, or your schema |
| Experts | Vetted by task interview; every trajectory tagged with the expert's role and tenure |
| Hosting | Environments run in your cloud or ours; data delivered to a US-region bucket |
Pick the workflow, the tools the agent will touch and what counts as done.
We replicate the workflow as an environment and validate it with the experts who will work in it.
Experts produce trajectories and preferences; verifiable rewards are wired where they exist.
Your model's rollouts are reviewed by the same experts, feeding the next batch.
Three questions. We reply within one business day with a sample set and a quote.