How to deploy AI agents and chatbots in your company: process, pricing and pitfalls

In short

• An AI chatbot answers customers; an AI agent also takes action on its own — records an order, creates a task, sends a quote
• The best results come from an agent connected to your own data and systems: e-shop, CRM, ERP, bookings, documents
• You start with one specific process, not “AI for the whole company”
• A customer support chatbot starts from €1,500, a custom agent with integrations from €5,000 (excl. VAT)
• Boundaries matter: what the agent may do on its own, what it only proposes and when it hands things over to a human

Most Slovak companies have already tried AI — in a ChatGPT or Copilot window. The real shift only happens when AI stops being a separate window and starts working directly with the company's data and systems. It answers a customer based on your current price list, finds the status of their order, logs an inquiry in the CRM or prepares a quote for approval.

In this article, we explain how to deploy such an AI agent or chatbot in your company: where to start, what the technical setup looks like, what it costs and what to watch out for. We draw on projects we deliver for companies in Slovakia, the Czech Republic and Austria.

Chatbot, AI agent or automation — what's the difference

AI chatbot

It answers questions in natural language — on the website, by email or in chat. A good chatbot doesn't draw on the model's general knowledge, but on your materials: price list, terms and conditions, products, FAQs. It typically handles customer support and first contact with customers 24 hours a day.

AI agent

An agent goes a step further — it doesn't just answer, it acts. It has access to tools: it can look up an order in the e-shop, check an open slot in the calendar, create a task in the CRM, fill in a form or prepare a document. It decides which tool to use when and returns the result to a person or customer.

Classic automation

A fixed “when A happens, do B” workflow (for example in tools like n8n or Make). It's reliable and inexpensive for repetitive tasks without exceptions. In practice, we often combine it with AI — automation keeps the workflow, AI handles the parts that require understanding text or making a decision.

Where AI agents make the most sense in a company

• Customer support — answers to recurring questions, order status, complaints, opening hours, product availability.
• Sales — qualifying inquiries from the website, logging them in the CRM, drafting a quote from the price list for a salesperson to approve.
• Bookings and appointments — checking an open slot and booking it right in the conversation.
• Document processing — reading invoices, orders or contracts and transferring the data into the system without retyping.
• Internal knowledge — an assistant that answers employees from internal policies, manuals and project documentation (RAG).

They have one thing in common: repetitive activities with clear rules that currently take people hours every week.

How an AI agent is deployed in 5 steps

1. Choosing the process. Together we pick one process with the greatest benefit — where there's a lot of repetition and results can be measured (number of questions handled, time saved, response speed).
2. Data and access. We determine where the agent will draw from (documents, database, e-shop, CRM) and what it will have access to. Sensitive data is addressed right at the start, not at the end.
3. Pilot. We build the first version on real data and test it on actual questions and cases, internally first.
4. Integration. We connect the agent to your systems via API or an MCP server and set up rules, logging and human handoff.
5. Operation and improvement. We monitor where the agent answers inaccurately or where people step in, and fine-tune it continuously. Team training is part of it too.

The technical setup: what's under the hood

The term “AI agent” covers several layers that have to work together:

• Language model — for example, models from OpenAI (GPT) or Anthropic (Claude). We choose based on the task, language and data protection requirements.
• Knowledge base (RAG) — your documents and data prepared so the agent can quote them accurately rather than make up answers.
• Tools and integrations — connections to the e-shop, CRM, ERP, calendar or accounting. Increasingly via MCP (Model Context Protocol), an open standard for connecting AI to business systems.
• Rules and oversight — what the agent may do on its own, what it only proposes for approval, when it hands the conversation to a human and how everything is logged.

We build the backend of these solutions on the Laravel and Symfony frameworks, which we also use for web applications and e-shops. So the agent isn't an isolated experiment but part of your system — with the same access management and backups.

How much an AI agent or chatbot costs

The price depends mainly on how many systems need to be connected and how complex the rules are. Indicative pricing (excl. VAT):

• AI chatbot for customer support — from €1,500. Answers from your materials on the website, including deployment and setup.
• Custom AI agent with integrations — from €5,000. Works with your systems and performs tasks.
• MCP server for your system — from €5,000. Makes your e-shop, CRM or database accessible to AI assistants such as ChatGPT and Claude.

On top of that, you need to factor in operating costs for using the language model, which depend on conversation volume. We always set the exact amount only after looking at the specific process.

What to watch out for

• Don't start too broad. “AI for the whole company” can't be delivered or measured. One process done well is a better start than ten half-done ones.
• Data quality is decisive. An agent is exactly as good as the materials it draws from. An outdated price list means outdated answers.
• Personal data protection. You need to know where data flows, where it's processed and what gets stored. This ties into GDPR as well as the rules of the European AI Act.
• Handoff to a human. Customers must always be able to reach a real person, and the agent must recognize when that's needed.
• Measure the results. Before launch, define what success looks like — otherwise the benefit will only ever be debated.

We write more about typical mistakes in our article The biggest mistakes companies make when adopting AI.

How we help with AI agents

At MR. Digital, we design, build and run AI solutions, and we train the teams that use them. We'll help you with the whole process:

• AI implementation — from process audit to production deployment,
• custom AI agents and chatbots connected to your systems,
• MCP servers that make your data accessible to AI assistants,
• AI training after which your team actually uses AI.

Frequently asked questions

What's the difference between an AI chatbot and an AI agent?

A chatbot answers questions from your materials. An AI agent also takes action — it has access to tools and can, for example, look up an order, book an appointment or create a task in the CRM.

How much does an AI chatbot for a business cost?

An AI chatbot for customer support starts from €1,500 excl. VAT. A custom AI agent with integrations into company systems starts from €5,000 excl. VAT. Operating costs for using the language model come on top.

How long does it take to deploy an AI agent?

A simple chatbot built on your materials can be launched within a few weeks. An agent with multiple integrations takes longer, so we start with a pilot on one process.

Does our data have to be in ChatGPT?

No. We design the solution so that only the data needed for a given answer reaches the model, and we choose models and settings based on data protection and GDPR requirements.

Can an AI agent be connected to our existing system?

Yes. We connect the agent via API or an MCP server to e-shops, CRM, ERP, booking or accounting systems. There's no need to change the software the company uses.

What if the AI agent gives a wrong answer?

The agent has set boundaries: it answers only from verified materials, only proposes sensitive actions for approval and hands complex cases to a human. All conversations are logged, so errors can be found and fixed.

Prices are indicative, excl. VAT, valid as of October 6, 2026.
Authors: the MR. Digital team