How do you know the simulation is right?
“If an AI wrote it, how do I know the numbers my students are shown are correct — and that next year's cohort sees the same thing?”
Atlas turns your prompt into a working app, and you refine it by asking for further changes. The AI personas then respond live during the session, every call routed through Vocareum's AI Gateway. Vocareum documents the governance around those calls — spend caps, no API keys in learner hands, an audit trail — but publishes no pre-publication review that freezes what a learner will actually see. Two students in the same scenario are having two different conversations, and so are this year's cohort and next year's. For conversational practice, that variation is the whole point. For a graded, quantitative exercise it means validation happens during the session rather than before it.
Bring Your Own Simulation reverses the order. You build the simulation wherever you like — with Claude, ChatGPT, or whatever your team already uses — on your own machine, and you iterate until the model behaves the way you would defend in a viva. Only then does it reach us, as a finished bundle of HTML, CSS and JavaScript. The upload wizard has five steps, and a student is on the far side of all of them:
- Details — name, description, discipline.
- Upload — every file is validated on arrival.
- Compliance scan — we check that the simulation reports its rounds and state back to the platform, so analytics and grading work.
- Test run — you open your own draft and play it exactly as your students will, as many times as you need.
- Submit for review — our team reviews every simulation before it goes live.
The difference is when validation happens: on Atlas, inside each session; with BYOS, before publication — by you first, then by us. And the simulations in Eureka's own catalogue run a deterministic engine, so identical decisions produce identical results for this cohort and the next — which is what makes a grade defensible in front of an accreditation panel.