AI for SMEs in Romania: where to start, step by step

If you run a small or medium-sized business in Romania, you have probably already heard that you "need to do something with AI". The trouble is that people rarely tell you concretely what, in what order and on what budget. The result: some owners put it off indefinitely, others buy a subscription to a fashionable tool that nobody is using after two weeks.

This guide shows you a simple, step-by-step path for an SME to get started with AI without risking much money and without turning the team upside down. It is not about technology for its own sake. It is about finding the place in your business where you lose the most money or time and putting a system there that works for you.

Why AI for SMEs is no longer just a topic for big corporations

Until a few years ago, a system that answers the phone, understands what the customer wants and takes down an order meant a software project lasting months. Today, language models such as Claude can hold natural conversations in Romanian, read documents and work with your business data through connectors. That lowers the barrier to entry considerably.

For a small business, the advantage is even greater than for a corporation. You have few people, everyone does a bit of everything, and every missed call or every hour spent copying data from one spreadsheet to another hits your turnover directly. A well-chosen AI system does not replace your team; it takes over the repetitive work that holds it back.

Step 1: Start from a problem, not a tool

The most common mistake is to start with the question "which AI should we use?". The right question is "where are we losing money or time every week?". Take a sheet of paper and, together with your team, write down the situations that keep coming up:

• Phone calls nobody answers at peak times or after hours.
• The same questions on WhatsApp every day: opening hours, prices, availability, address.
• Orders or appointments written on paper and lost along the way.
• Data entered two or three times into different systems (Excel, invoicing, email).
• Quotes or reports that take hours because they are done by hand.

For each situation, estimate how often it happens and what it costs you. You do not need precision, you need the order of magnitude. A real example: a chain of cake shops in Sibiu was losing around 20 calls a day, and each unanswered call was often a lost order. The problem was clear and measurable, so the solution was easy to justify.

Step 2: Choose a single process to begin with

Do not automate everything at once. Choose a single process that meets three conditions:

1. It happens often – daily or several times a week.
2. It has clear rules – you could explain to a new starter, in 15 minutes, how to do it properly.
3. It has a measurable outcome – calls answered, appointments booked, hours saved, orders logged.

Processes that tick all three are the best candidates for a first project. In SMEs, these are usually answering calls, replying on WhatsApp, booking appointments, entering orders or sending standard quotes.

Step 3: Match the problem to the type of solution

Once you know what you want to solve, choosing a solution becomes much simpler. Here is roughly how common problems map to types of system:

Prices are indicative, excluding VAT, and paid in instalments tied to deliverables. Monthly costs (infrastructure, usage, maintenance) depend on volume, so you set them once you know how many calls or messages will be processed.

Step 4: Prepare the information the system needs

An AI agent is only as good as the information you give it. Before implementation, gather:

• Your list of products or services, with up-to-date prices.
• Opening hours, addresses, delivery or booking terms.
• The 20–30 most frequent questions from customers, with the correct answers.
• Business rules: what the system can promise, what it cannot, when it transfers to a person.
• Access to the apps it needs to work with (calendar, order spreadsheet, CRM).

They do not have to be perfect. They have to be written down. Often, the very exercise of putting your business rules on paper reveals inconsistencies you had anyway, with or without AI.

Step 5: Start with a short pilot and measure

Your first system does not have to be final. Start with a pilot of a few weeks within a limited scope: one location, one phone number, or only messages after hours. Decide in advance what you will measure:

• How many calls or messages the system handled.
• How many turned into orders or appointments.
• How many were transferred to a person, and why.
• What complaints or confusion came up.

During the pilot, someone on the team needs to read the conversations every day. That way you quickly find where the system answers wrongly or incompletely and correct the instructions. After two or three weeks of adjustments, the difference in quality is usually very large.

Step 6: Involve your team from the start

Your people may fear that AI is coming for their jobs. Tell them directly what the system does and what it does not do. A voice agent that handles routine calls does not replace the shop assistant; it frees her from the phone ringing while she is serving a customer. A chatbot does not replace the adviser; it sends them customers who are already qualified.

Appoint one person responsible for the system: someone who reads the conversations, flags problems and suggests improvements. They do not need to be technical, they need to know your customers and processes well.

Step 7: Only expand what works

After the pilot you have real numbers. If the system delivers, you expand it: to all locations, to more hours, to more types of request. Then you move on to the next process on the list. Over time, many businesses end up with an ecosystem: a voice agent that takes orders, an ERP they flow into automatically, WhatsApp notifications for customers.

The Sibiu cake shop example follows exactly this path: a voice agent that recovers missed calls and a custom ERP that orders go into in a structured way. A hospitality client in Cluj started with its own AI agent so it could take direct bookings instead of paying around 20% commission to booking platforms.

Common mistakes when an SME starts with AI

• Too much, too fast. Five projects in parallel usually means five half-finished projects.
• No one in charge internally. Without someone keeping an eye on the system, quality drops over time.
• Unreliable data. Old prices or contradictory rules lead to wrong answers.
• Expecting "magic". An AI system is very good at clear, repetitive tasks, not at strategic decisions.
• Ignoring data protection. Always ask where customer data is stored and who has access to it.

What data security means in practice

When an AI system talks to your customers, it processes personal data: names, phone numbers, addresses, sometimes order details. You have the right to know exactly what infrastructure everything runs on. At Neurotech, agents run on Claude (Anthropic), and data is stored in Supabase databases on EU servers. You will find the details on our data security page. Any serious supplier should be able to explain the same thing to you, clearly and in writing.

Quick checklist: are you ready to start?

• You have identified a process that repeats and costs you money or time.
• You can estimate, at least roughly, what it costs you now.
• You have the basic information written down: prices, opening hours, FAQs, rules.
• You have someone on the team who will keep an eye on the system.
• You know which number you want to see improve after the pilot.

If you have ticked at least three, you are more ready than you think.

Next step

If you want to find out what the best first AI project for your business would be, we can talk for 30 minutes, free and with no obligation. Tell us how you work now, and we will tell you honestly whether, and where, an AI system is worth it. You can book a call here.