AI agents for businesses

An AI agent is a system that understands a request in natural language and, instead of just answering, takes the steps needed to resolve it: it checks data, uses tools and completes tasks in your systems. When you give that agent a defined role (duties, permissions and rules about what it must check first), you have a digital employee.

The agents we build aren't demos. They work in production, with real clients, in law firms, car dealers and service companies.

Which AI agents we build

Customer service

It answers your clients' questions by email, WhatsApp or chat with real information: the status of their order, their file or their appointment. When a request falls outside what's expected, it hands over to your team with the case summarised instead of making up an answer.

An assistant with your company's knowledge

It answers your team using internal documentation: procedures, template contracts, commercial terms, applicable regulation. It cites where each answer comes from so it can be checked.

Reading and sorting documents

It reads invoices, contracts, payslips, IDs or deeds; extracts the relevant data; checks the documents are complete and files them in the right place. If something is missing, it asks for it.

Sales

It qualifies incoming leads, answers within minutes at any time, proposes a meeting based on the salesperson's calendar and leaves a summary of each conversation in the CRM.

From agent to digital employee

The difference between an agent that impresses in a demo and one you can leave working lies in the design around the model:

• A role, not a chat. Each agent has its list of authorised capabilities and sees no others.
• Human approval. Sending something to a client, changing data or communicating a decision waits for a person to approve it.
• A written success criterion. Before a request starts, what counts as done well is defined, and the result is checked against it.
• Calculations with rules. Amounts, deadlines and counts are calculated by the system with programmed rules, not by the model.
• Memory per case file. Everything that happens in a case is logged with its author, so the agent picks up where it left off and you can audit it.

We explain it in detail in what is a digital employee.

How we build it

1. 01

   Pick the right task

   We look for work that eats hours today and requires reading or interpreting. If the rules are fixed, we propose an automation, which costs less.

2. 02

   Define the role

   Which requests it receives, through which channels, which capabilities it needs and what a person must always approve.

3. 03

   Test with real cases

   Before going live, we evaluate it with real examples from your company, difficult ones included.

4. 04

   Supervise and improve

   During the first weeks we review each decision with your team and adjust instructions and permissions.

Data and compliance

Your data is treated as what it is: confidential information about your company and your clients. Each company's data is isolated, we use the models through business APIs that don't train on your data by default, and we design every agent with the GDPR and the EU Artificial Intelligence Act in mind. There's more detail in AI agents in business: risks, human oversight, GDPR and the AI Act.