Simbox trains your people through deliberate practice — realistic simulations of real work, reviewed after every session. Then it measures the change.
Fig. 01 — The before/after your board asks for.
Ninety minutes per person. Now you know where you actually stand.
Realistic work simulations with planted errors and live interruptions, reviewed after every session. Streaks and quests make it a daily habit.
Skill change per person, per team, from evidence you can open and read.
Exercises like Know Your Models train the judgment: which model class for which job, what each gets wrong, and what it costs. Content is validated against current models and refreshed when they change.
| The job | Frontier model | Fast & cheap | Open-weights, on-prem |
|---|---|---|---|
| Deep analysis | |||
| Quick drafts, bulk work | |||
| Working with code | |||
| Sensitive data | |||
| Niche facts, no sources |
Fig. 02 — The judgment the exercises train. Bottom row included on purpose.
A library across eight roles — plus your own scenarios, built from your real documents, private to your workspace. Details regenerate per attempt; only the scoring stays fixed.
Fig. 03 — Same engine underneath: practice predicts assessment.
Results arrive pre-scored; a keyboard queue for the flagged few.
A monthly AI budget per workspace. It degrades gracefully, never bills surprise.
Scenarios from your documents are private to your workspace.
Role-appropriate, documented AI literacy — Article 4, with an audit trail.
A guided walkthrough with sample data — the team view included.
See the team view