What is an AI employee?

A role, not a tool.

A tool waits for a prompt. An AI employee has a job.

It handles one recurring task: reading the relevant information, preparing work and asking for human approval where required. It uses the team’s approved examples and corrections. Managed AI describes who runs the service; AI employee describes the task it performs.

Mia is Rebotify’s own AI intake role. The AI employee we set up for your business has an agreed task, such as preparing support replies, following up sales enquiries or checking contract documents.

A named role makes the task easier to identify and review. Your team can see what work is waiting, who should approve it and where to raise a problem with Rebotify.

Buyers often arrive from searches for AI receptionist or virtual receptionist. Those terms describe the front-desk job; AI receptionist and managed AI describe how Rebotify delivers it. For law firms, the concrete example is a legal intake employee or virtual receptionist for law firms: approved scripts, after-hours calls, web enquiries, consultation booking, transcripts, and matter handoff before a lawyer gives advice.

What an AI employee actually does.

It starts where the team already feels pressure: support replies, CRM follow-up, document checks, intake, reports, or handoffs.

The AI employee uses your enquiries or documents to prepare the agreed work. Your team’s corrections and unusual cases inform updates to its written instructions.

In production, AI employees we have shipped run workflows like inbox triage, enrolment follow-up, first-line ticket triage, and legal document assembly. Each is one named role, one workflow, one approval rhythm. The work scales by adding trusted workflows to the role, not by launching fleets of unsupervised agents.

If volume later justifies a second role, it gets its own scope, name, memory, and approval rules. That is different from buying a fleet of agents before the first employee has earned trust on one job.

The buyer should not manage prompts, connectors, monitoring, or model changes. That is why Rebotify sells a managed AI employee, not a platform license.

Read the case studies: case studies.

How your instructions and feedback are retained.

Each AI employee uses a record of your approved examples, corrections, unusual cases, tone and rules for passing work to the right person.

That record preserves your team’s agreed way of working when tools or AI models change.

If the underlying AI model changes, the record of your rules, approved examples, corrections and requests for human help remains. The service can continue using your team’s agreed way of working.

How it is priced.

Choose per-task pricing for completed work, such as a contract check or support request sorted for review; a flat monthly price for ongoing work; or a base setup cost plus an agreed share of revenue from closed deals for sales work.

Tokens are our cost basis. They are not the unit we sell. The unit we sell is the work.

You can compare the agreed price with completed work, such as documents checked, replies prepared, reports drafted or consultations booked. Rebotify handles the underlying AI processing costs.

Month-to-month for general workflow plans. Vertical intake plans may include setup when scripts, routing, and handoffs need to be built up front.