What an AI Agency Actually Does and How to Choose One (2026)

The supply of AI services in Croatia has grown faster than any yardstick you could use to judge who actually delivers what. If you are looking for an automation partner, it is more useful to understand what the work concretely involves and which questions to ask before you sign than to compare promises on homepages.

What an AI agency does in practice

Serious work does not begin with picking a model or a tool. It begins with a review of how the company works today: where the same data is retyped by hand from one system into another, which documents are produced by editing last year’s version, where customer enquiries sit waiting because nobody is explicitly responsible for them. That review produces a list of the work worth automating, with an estimate of the hours currently spent on it.

Only then is the technology chosen. An agent is a program that carries out a task on its own, according to rules you have set: it reads an email, recognises what it is about, opens a case, drafts a reply and reports what it did. One agent is a tool. Several agents working on the same data and handing work to one another are already an operating system, and that is where the real difference in results appears.

Six areas where this is done most often today

An overview of all six areas, with examples and indicative pricing for the first step, is on the AI business process automation page.

• AI operating systems — a company’s documents, processes, communication and knowledge connected into a single whole.
• Email and communication agents — classification, processing, delegation and tracking of messages, enquiries and leads.
• Purpose-built agents — for SEO, content, research, regulatory compliance, sales or operations.
• Documentation and compliance — procedures, reports, onboarding of new employees and regulatory processes without manual work.
• Knowledge systems — email, documentation, notes and CRM in one searchable place.
• AI infrastructure — local or in the cloud, set up, integrated and maintained.

Five checks before you sign

1. Proof you can inspect yourself

A presentation can be put together in an afternoon. A system running in production cannot. Ask them to show you live something that runs every day, and ask what happens when it fails. The answer to that second question reveals how much experience sits behind the story.

2. Who carries the risk of the rollout

If the entire build is billed up front with no conditions attached, the risk sits entirely with you. Ask whether there is a period in which the system has to prove it works by your rules before you pay for it. A guarantee the agency offers on its own says a great deal about how much it trusts its own work.

3. Where the data is stored and processed

Before work starts it should be clear which data leaves your company, which services it is sent to and how long it is kept. That is a question for the contract, not for a conversation after the first incident — especially if you work with employee records or client data.

4. What stays with you

Ask what is yours if the engagement ends: the written plan, the documentation, the access, the rules the agent works by. A system you cannot take over is not automation of your business, it is permanent dependence on a supplier.

5. How many clients they run at the same time

A rollout requires presence in the first weeks, while the rules are being set and corrected against real cases. The answer to this question tells you fairly precisely how much time and attention you will realistically get.

Why a local partner has the advantage

A Croatian company works with documentation in Croatian, with domestic regulation and with people who talk about their work in their own language. An agent that processes messages or documents has to understand that language and that context, and whoever builds it has to understand how business actually runs here. On top of that, a partner in the same time zone can come to a meeting and sit down next to the people who will use the system, which in the first weeks is worth more than any documentation.

How we work

DigitalBees is an AI-native agency: we build automation with a swarm of agents rather than with individual tools. Our main proof of capability is this ecosystem itself. The site you are reading was built and published by AI, this article was written and checked by an agent from the swarm, and the social posts are handled by another agent. Both this text and the system that publishes it were produced in the same way we build client systems, so you can inspect them before you trust us with anything.

The consulting is led by Petar Kaić, who has run Anparo for sixteen years and knows occupational safety work first-hand, alongside the SEC Anparo education institution and a food service business in an entirely different industry. He is not a developer and considers that an advantage: he does not offer technology he happens to like, he first establishes where the client loses the most time, and the tool follows from that. The code is written by agents and the team.

We keep the risk of the first phase on our side. If after the assessment you do not have a list of at least three processes worth automating — each with hours, a deadline and a price — you pay nothing. You pay for an agent only once it has run for two weeks by your rules, and monthly management comes with no minimum term. We work with four companies at a time, so the number of places is limited.

If you are considering automation, start with the question of where most of your weekly hours go on work nobody would choose to do. The first call takes about thirty minutes and exists precisely so we can work that out together — including telling you if it is not worth doing.

How quickly can an AI agency show a first result?

That depends on the process, but the first measurable step is an assessment with a list of processes, hours, a deadline and a price. Only once that list exists does it make sense to talk about deadlines for an individual agent.

Does automation work even if our data is not in order?

Messy data is the usual starting point, and putting it in order is part of the job. What matters more is having someone who knows how the process actually runs, because the agent’s rules are written against that reality rather than against the ideal description in a procedure.

Does automation mean we will be reducing headcount?

Our position is the opposite: AI removes pointless manual work so people can focus on what genuinely matters. Retyping data and assembling reports by hand are not the jobs you hired someone for.

Frequently asked questions

Can you show client references we can check?

We have no public references with client names yet, and we do not use invented case studies. Instead we show you our own system: this site, the blog and the social posts are produced and published by our swarm of agents, and the system’s work is visible in a public activity log. Once clients give us permission, we will add their results too.

What happens if an agent does not work the way we agreed?

You pay for an agent only after it has run for two weeks by your rules. If it does not pass that mark, you pay nothing. The initial assessment carries an unconditional guarantee: if afterwards you do not have a list of at least three processes worth automating — each with hours, a deadline and a price — you pay nothing and we ask for no explanation.

Do we need our own IT department to get started?

No. The code is written by agents and our team; your role is to explain how the work runs today and to confirm the rules the agent is allowed to follow. If you do have an IT department, we work with it and hand the system over in a state it can understand.

How many clients do you work with at the same time?

Four. Rolling out automation needs heightened presence in the first weeks, while the rules are being set and adjusted, so we keep the number of places limited rather than growing faster than we can follow.

What does the first step look like?

A call of about thirty minutes in which we go through your processes and establish whether automating anything makes sense at all. If it does, the next step is an assessment with a written plan that stays yours — even if we do not continue working together.