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AI agents

AI agents for business that do the work, not just answer

An AI agent is a virtual assistant that understands a request in a customer's own words and sees it through to the end: checks a slot in the calendar, creates a customer card in the CRM, prepares an offer or passes the case to the right person. It works in your systems, by your rules and within the permissions you give it.

What is an AI agent

What an AI agent is

A chatbot answers, an AI agent acts

A classic chatbot knows answers. An AI agent also has access to tools – calendar, CRM, email, spreadsheets, the order system – and can plan several steps in sequence. In business terms: it's not a box with answers, but a worker for repetitive tasks who doesn't get sick and doesn't forget.

Understands the request

The customer writes or speaks however is convenient for them. The agent recognizes what the request is about, asks for missing details and doesn't require clicking through a rigid menu.

Uses tools

It reads and writes data in the systems it has access to: checks availability, creates a booking, updates a status, sends a confirmation.

Runs multi-step tasks

Receive an inquiry, check the customer in the CRM, prepare a quote, send it and set a reminder – that's one task for an agent, not five separate automations.

Knows when to hand off

A complaint, an unusual request, a financial decision – the agent passes the case to a person together with the context, instead of guessing.

Types of agents

Which AI agents we deploy in companies

Each of them can be launched on its own. Most often we start with one process and add further agents on the same knowledge base and the same integrations.

01

Customer service in chat

  • Website, Messenger, Instagram, WhatsApp, Telegram
  • Answers from your price list and terms
  • Bookings, orders, case status
  • See AI chatbots →
02

AI voice agent

  • Answers calls around the clock
  • Books appointments and takes orders
  • Integration with the phone exchange, CRM and calendar
  • See AI voice agents →
03

Sales agent

  • Qualifies leads from forms and messengers
  • Creates the contact and sales opportunity in the CRM
  • Reminds about follow-ups and books a call
04

Back-office agent

  • Reads invoices, orders and forms
  • Fills in the CRM and spreadsheets without retyping
  • Recurring reports and summaries
  • See process automation →
05

Company knowledge agent

  • Answers from procedures, contracts and instructions
  • A source with every answer
  • Faster onboarding of new employees
  • How RAG works →

Security

An agent that works in your systems needs boundaries

The more an agent can do, the more important it is what it can't do. We set these rules before launch, not after the first incident.

Minimal permissions

The agent gets access only to the data and operations its task requires. A booking bot doesn't see invoices, and an invoice bot doesn't send emails to customers.

Human in the loop

Operations with financial or legal consequences – a discount, a refund, sending an offer above a set threshold – the agent prepares and an employee approves.

Logs of every action

Every conversation and every operation in a system is recorded. You can see what the agent did, on what basis and where it failed – the foundation for improvements.

GDPR and local models

We process data in line with GDPR, under a processing agreement. Where data shouldn't leave the company, the agent can run on a local LLM on your infrastructure.

AI Act compliance

The agent says it is an AI assistant, and we prepare the implementation documentation. More about the obligations in the article AI Act in Poland.

Implementation

From one process to a working agent

We launch the first working version in 7–14 days. We describe the whole process on the page AI implementation in a company.

  1. 01
    Choosing a process

    We look for a task that is repetitive, takes the team a lot of time and has clear rules. We write down how it looks today, who is involved and where a decision begins that the agent shouldn't make on its own.

  2. 02
    Knowledge and integrations

    We gather the documents the agent should use and connect the systems: CRM, calendar, phone exchange, email, messengers. We set the permissions and the points where a person approves an action.

  3. 03
    Testing

    The agent first works on test scenarios and in preview mode: it prepares actions but doesn't carry them out. We fix the places where it goes wrong and only then switch on the full scope.

  4. 04
    Growth

    Every month we review the logs, extend the knowledge base and widen the scope with further tasks. In the subscription this work is a standing part of the service, not a separate project.

FAQ

AI agents – questions

How does an AI agent differ from a chatbot?

A chatbot answers questions based on the knowledge it was given. An AI agent also performs actions in systems – books, saves, sends, updates – and can combine several steps into one task. In practice the line is blurry: a good chatbot integrated with a calendar is already a simple agent.

How much does it cost to implement an AI agent?

We bill an AI agent by subscription – in the Basic, Standard and Maximum packages, depending on the number of channels, integrations and traffic volume. Cost is driven most by integrations with your systems, not by the language model itself. A PARP (Polish Agency for Enterprise Development) grant can cover up to 75% of implementation costs.

Which systems can the agent work with?

Most often CRM, calendar, phone exchange, email and messengers. If a system has an API, connecting it is usually simple. If it doesn't, we look for another way, for example through a data export or an email inbox, and we tell you plainly when such a solution would be too fragile.

Can an AI agent make mistakes?

Yes, like any system built on a language model. That's why we limit its knowledge to your documents, give it minimal permissions and leave decisions with financial consequences for a person to approve. Every action is saved in the logs, so an error can be found and fixed quickly.

Will company data go to external AI providers?

It depends on the chosen model, and we settle this before implementation. With cloud models we take care of processing agreements and GDPR compliance. If data shouldn't leave the company, the agent can run on a local LLM installed on your server or in your office.

First agent

Let's pick one process for an AI agent

At the consultation we'll go through the tasks that take up your team today and point out the one to start with. We'll also show you what an agent would look like on your data. No obligations.