Start with a role, not a model
An AI employee begins with a job that a team can describe and supervise. The role may qualify inbound leads, answer support questions, coordinate appointments, collect intake information, or keep an operational queue moving.
The model is important, but it is only one component. The operating design around it determines whether the employee is useful, repeatable, and accountable.
The six parts of a deployable employee
Aivah treats an AI employee as a connected system. Each layer answers a practical business question before the role is published.
- Role: what outcome is the employee responsible for?
- Knowledge: which approved sources may it use?
- Presence: should it appear through text, voice, phone, an avatar, or a live character?
- Tools: which actions and systems are permissioned?
- Memory: what context should persist, and under which rules?
- Management: who reviews conversations, outcomes, exceptions, and handoffs?
Why channels change the work
A role behaves differently on a landing page, a phone call, WhatsApp, Slack, or an embedded live-character surface. Good deployment preserves the same knowledge and boundaries while adapting the interaction to the channel.
That is why publishing is not the final technical step. It is part of the employee design: response length, identity, escalation, consent, and context all need channel-aware decisions.
Pilot one measurable workflow
The safest starting point is a contained workflow with a visible outcome. Define what success looks like, what the employee may do, when a human takes over, and what evidence the team will review.
Once that loop works, the same employee can gain more knowledge, channels, tools, and responsibility without losing its operating boundary.