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Your AI employee is trained to sound like your brand and operate by your rules — not generic AI defaults. Before your AI employee handles its first task, Jobr works with you to understand how your business communicates and what policies govern your day-to-day operations. That knowledge is built into your AI employee’s behavior from the start, so it responds the way you would, enforces the policies you’ve set, and represents your business the way you want it represented.

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Tone of voice

The way your AI employee communicates is as important as what it says. A mismatch in tone — too formal, too casual, or simply off-brand — can undermine the customer experience even when the information is correct. Tone training ensures your AI employee sounds like a natural extension of your team.

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What tone training covers

  • Formality level — Whether your brand speaks in polished, professional language or a more relaxed, conversational style.
  • Vocabulary — Industry-specific terms, phrases your customers expect, and words or expressions you want to avoid.
  • Sign-off style — How your AI employee closes a conversation or message — from a warm sign-off to a concise confirmation.
  • How to address customers — First name, last name, formal title, or something else — whatever fits your customer relationships.

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How to define your tone

During onboarding, Jobr asks you to share examples of your existing customer communications. These might include past email threads, live chat transcripts, FAQ responses, or any other written material that reflects how your team communicates today. The more examples you provide, the closer the AI’s natural voice will be to your own. If your brand voice has evolved, or if you simply want to refine how your AI employee sounds, you can request tone adjustments at any time through your Jobr account manager.
The more examples you provide during onboarding, the more accurately the AI will match your brand voice. A handful of real customer emails or chat transcripts goes a long way.

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Business policies

Your AI employee doesn’t just communicate in your brand voice — it also follows your business rules. Policies cover everything from how refunds are handled to how appointments are booked, and they are encoded directly into the AI’s behavior so it operates consistently, every time.

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What policy training covers

  • Return and refund policies — The conditions under which refunds are approved, the process for handling returns, and any exceptions.
  • Pricing rules — Published prices, package structures, and any discounting policies (including what the AI can and cannot offer).
  • Service-level agreements (SLAs) — Response time commitments, resolution windows, and any promises made to customers about how quickly things get done.
  • Cancellation terms — The rules governing cancellations, notice periods, and any associated fees or conditions.
  • Scheduling rules — Booking windows, availability constraints, lead time requirements, and how rescheduling is handled.

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How policies are documented and maintained

Your policies are documented in detail during the role mapping phase. Jobr works through each policy area with you, asks about edge cases, and translates the rules into the AI employee’s operating logic. Once live, the AI follows those policies consistently — it doesn’t improvise or make exceptions. When a policy changes — whether it’s a new refund threshold, updated cancellation terms, or a revised SLA — you need to notify your Jobr account manager so the AI employee’s training can be updated. Policy changes are not automatic. Until the update is applied, your AI employee will continue operating under the previous rules.
Review your AI employee’s first week of responses carefully. If anything sounds off-brand or doesn’t reflect your policies correctly, flag it immediately so Jobr can make adjustments before the behavior becomes a pattern.