Roles and responsibilities
Each digital employee has an explicit scope and permission boundary; when a boundary is unclear the orchestration layer refuses rather than improvising.
Writing a prompt for one agent is easy. Getting five agents to collaborate by role is not. OfficeMind makes roles, responsibilities, task flows and hand-offs into orchestrated objects, so an AI team behaves like an organisation.
Once a task is split across agents, new questions appear immediately: who owns what, what upstream hands over, how downstream receives it, and who is accountable when it fails. Human organisations solve this with job descriptions; AI teams usually skip it.
Each digital employee has an explicit scope and permission boundary; when a boundary is unclear the orchestration layer refuses rather than improvising.
Inputs and outputs between steps are explicit contracts. If hand-off conditions are unmet the task stops rather than producing a half-finished artefact.
Knowledge is mounted per role, avoiding a full background dump into every agent — keeping both cost and noise under control.
Every call, duration and output is recorded, so a failure can be traced to a specific step instead of being judged by the final result alone.
Design boundaries today
| Dimension | Notes |
|---|---|
| Shape | Multi-tenant SaaS; each tenant gets its own roles and task configuration |
| Model layer | Pluggable and routed per task, with no single-vendor lock-in |
| Observability | Per-task cost and quality metrics, to judge whether AI should own this job at all |
| Status | In beta; treat the capability boundary as what actually works today |
Product summary
| Item | Detail |
|---|---|
| Status | Beta |
| Product | OfficeMind (OfficeMind) |
| Standalone site | https://officemind.zyaisoft.xyz/ |