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Services / AI workers

AI workers that take over a role's repetitive work.

An AI worker does the routine part of one role. A person approves what matters, and quality is measured on your own tasks.

Book a callAI engineering

01 / Problems

Problems we solve

Typical starting points. This page is about agents for a defined role; the engineering frame around them is on the AI engineering page.

  • Copy and paste between systemsPeople move data from mailboxes and documents into the ERP all day, and the volume rises with the business.
  • Rules that live in people's headsThe checks that make a result correct are known by a few colleagues and are applied unevenly.
  • Pilots nobody can judgeAn agent demo looks good, but nobody can say how often it is right on your real cases, or what happens when it is not.
  • Fear of an unsupervised systemYou want the time back, but not at the price of an agent that changes records without anyone looking.

Without an AI worker

  • People copy data between systems all day
  • The rules live in a few heads
  • Nobody can say how often it is right

With an AI worker

  • The routine part is prepared for you
  • Your rules are applied every time
  • Quality is measured on your own test set

02 / Roles

Roles an AI worker can take on

Each role is scoped to one process, with the systems it reads from, the action it proposes and the person who decides.

  • Order intakeReads orders from e-mail and attachments, checks them against customer and product data and prepares the order for your system.
  • Customs paperwork checksCompares the documents of a shipment with each other and with the declaration data, and flags gaps and mismatches before submission.
  • Invoice matchingMatches purchase invoices to orders and receipts, and passes exceptions to the person who handles them.
  • Planning proposalsPrepares a planning proposal from open orders and your rules, so a planner reviews and adjusts instead of starting from blank.
  • Customer e-mail triageSorts incoming messages, drafts a reply from your own information and routes what needs a person.
  • Master data clean-upFinds duplicates and inconsistencies in customer, product or supplier data and proposes corrections for approval.

What we automate

What we automate, in practice

Five roles an AI worker can take on: answering customer questions, taking orders, checking invoices, keeping master data clean and proposing a plan. A person approves what matters.

NexOps workspaceCustomer questionstoday · 10:42Demo data

Shared mailbox

  • buyer@demo-customer.example10:38Where is my shipment?Sent
  • office@demo-retailer.example10:21Damaged goodsComplaintAssigned to the complaints owner
  • depot@demo-wholesale.example09:47Change of delivery addressDraft ready
  • finance@demo-supplier.example09:15Question about an invoiceDraft ready

Where is my shipment?

buyer@demo-customer.example → service@demo-company.example · 10:38

Hello, can you tell me where order ORD-2029 is? We expected it this morning.

Kind regards, the buyer

Status from the TMS · ORD-2029

  1. Loaded08:10
  2. In transitnow
  3. ETA14:30

Reply draft

Hello, thank you for your message.

Order ORD-2029 was loaded at 08:10 and is in transit. The expected arrival is 14:30 today.

Kind regards, customer service

Sent by a colleague

Next in the mailboxQ-3309 Damaged goods: photos attached, complaint opened

Every reply is a draft that a colleague sends. Complaints go to the right person with the history attached.

03 / How it works

From role to worker

The same steps for every role. Plan and quote follow a first conversation.

  1. Define the role

    We write down the tasks, the inputs, the rules and the point where a person decides. One role at a time.

  2. Connect your systems

    The worker reads and writes through the interfaces of your mailbox, ERP and planning tools, with the rights of a named service account.

  3. Build a test set

    We collect real cases with the answers your team would give, so quality is measured on your work and not on a generic benchmark.

  4. Run beside the team

    The worker proposes and a person approves. We compare its proposals with the decisions people make, and tune until the gap is acceptable to you.

  5. Widen with evidence

    Only the cases where the measured quality is good enough move to lighter review. The rest stay with a person.

04 / Human in the loop

A person stays in control

An AI worker is a colleague that prepares work, not an unsupervised process. These controls are part of every build.

  1. InputsE-mail, documents, orders
  2. AI workerReads, checks, proposes
  3. A person approvesDoubtful cases go here
  4. Your systemsEvery action logged
  • Actions with consequences, such as a booking or a message to a customer, wait for approval until the measured quality supports less review
  • Every proposal shows the source it used and the rule it applied, so the reviewer can check it quickly
  • Low confidence and unusual cases go to a person instead of being guessed
  • Every action is logged with who or what did it, so you can audit and reverse it
  • The worker runs with least privilege: only the systems and fields its role needs
  • A person can pause or switch off a worker at any time

05 / Evaluation

Measured with our evaluation harness

Quality is a number you can read, not an impression. The harness runs the worker against your test set on every change, so a new model or a new rule cannot quietly make it worse.

  • A test set built from your own cases, with the answers your team would give
  • A regression gate in the delivery pipeline: a change that lowers quality does not ship
  • Traces of every step, so a wrong answer can be found and explained
  • A review of the cases where people and the worker disagree, which feeds the next improvement

AI harnesses and frameworks Voice agents for phone work

Estimate

Estimate the time you could free

Enter your own numbers. The calculator multiplies them and shows the result. It has no default figures of its own.

Use your own count, for example from last month.

Tasks are the units of the role you have in mind, for example orders or invoices.

Salary plus overhead, for the people who do this work.

Your estimate

Fill in the three numbers and set the share to see your estimate.

06 / Proof

Related work

The case below is about document processing, a task AI workers build on.

All projects

FAQ

Questions about this service

What is the difference between an AI worker and a chatbot?

A chatbot answers questions. An AI worker has a defined role in a process: it reads inputs, applies your rules, connects to your systems and prepares or performs an action, within limits you set and with a person who approves what matters.

Will it change records without anyone checking?

Not unless you decide so. We start with proposals that a person approves. Only cases where the measured quality supports it move to lighter review, and every action is logged.

Which systems can it work with?

Mailboxes, your ERP or accounting system, planning tools and document stores, through the interfaces they offer. We confirm what is possible in discovery.

Where does it run, and where does the data go?

In your own Azure tenant or EU environment. We do not send your data to external AI services without your written agreement. If you need it, we can run open-weight models on infrastructure you control.

How do you know it works?

We measure it on a test set made from your own cases, before go-live and on every change. We do not promise a result in advance: the first measurement shows what is realistic for your process.

Can you also run it after go-live?

Yes, under a written agreement. It covers monitoring, updates, small changes and support. It is optional.

Next step

Which role would you hand over first?

Tell us about one repetitive role in your operation. We will say whether an AI worker fits and what a first measurement would involve.

Book a callSend a messageor email info@nexops.nl directly

Currently accepting projects for Q4 2026