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Sectors

Every sector has its routine

An AI worker takes it on, shaped around how your company works. Here's what it typically handles, sector by sector.

Let's talkScenarios

01 / 06

Healthcare & clinics

The schedule: bookings, changes and reminders, so the front desk can focus on patients.

Typical tasks

  • Booking and rescheduling visits
  • Reminders the day before
  • Cover when a doctor is absent

02 / 06

Retail & e‑commerce

Customer questions and order follow-up, day and night.

Typical tasks

  • Order status and stock answers
  • Reminders about unpaid orders
  • Returns and exchanges

03 / 06

Finance & accounting

Documents and payments: matched, checked and ready for approval.

Typical tasks

  • Matching invoices to orders
  • Preparing payments for approval
  • Reminders about overdue payments

04 / 06

Logistics

Orders and delivery status without manual data entry.

Typical tasks

  • Partner orders from emails and spreadsheets
  • Answers on delivery status
  • Checks against stock and prices

05 / 06

Professional services

From first request to consultation and paperwork, nothing gets lost.

Typical tasks

  • Qualifying requests
  • Booking consultations
  • Sorting incoming documents

06 / 06

HR & recruiting

Candidates get an answer right away, recruiters get ready profiles.

Typical tasks

  • A first reply to every candidate
  • Interview booking and reminders
  • Candidate profiles in your system
The principle

The sector changes the details. The principle stays the same: the AI worker takes the routine, your people keep the decisions.

Scenarios

What it looks like in practice

Four typical situations. From signal to result, with no one involved until a decision is needed.

  • Retail01

    “Where's my order?” at 11 pm

    1. A customer writes in the channel they already use
    2. The AI worker finds the order and its delivery status
    3. ResultReplies with the date and flags any delay to the manager

  • Finance02

    An invoice that doesn't match

    1. A supplier's invoice arrives by email
    2. Matched against the order: one item differs
    3. ResultPayment prepared; the accountant approves or rejects it

  • Logistics03

    An order in a spreadsheet

    1. A partner sends an order as a spreadsheet
    2. Items checked against stock and prices
    3. ResultOrder entered into your system, partner gets a confirmation

  • HR04

    A candidate applies at night

    1. An application arrives after hours
    2. The AI worker replies and asks three short questions
    3. ResultInterview added to the recruiter's calendar

Typical scenarios on fictional data.

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