AI applied to real problems

AI solutions that start with the way you work

We identify a repetitive task or concrete opportunity, design the workflow and validate it with you before automating. The proposal depends on the diagnosis and does not promise automatic results.

From problem to solution

  1. 01A brief diagnosis of the process, objective and constraints.
  2. 02A proposed workflow, required data and human control points.
  3. 03A case-specific demonstration or prototype, when applicable.
  4. 04Implementation only after scope, price and responsibilities are agreed.

Which problem do you want to solve?

Concrete examples of how a solution may be structured. Every case requires technical and commercial validation.

Repetitive support

Your team spends time answering the same questions.

Example: an assistant trained on company FAQs and documents, with human handoff when required.

Inconsistent marketing

Planning, producing and adapting content across channels is difficult.

Example: an editorial workflow that turns one approved topic into a post, carousel, email and distribution calendar.

Leads without follow-up

Contacts become fragmented and opportunities do not receive timely follow-up.

Example: initial qualification, request summary and follow-up tasks for the sales team.

Manual administrative work

Copying data, organising requests and preparing reports takes hours.

Example: structured data collection, validation and report generation for human review.

Working demonstrations

Explore XMill environments that show current capabilities. These are demonstrations, not case studies or performance guarantees.

15 minutes

Request an initial diagnosis

Tell us where time is being lost or what you want to improve. The conversation is used to understand the problem and decide whether a proposal makes sense.

  • No obligation to hire
  • Focused on one concrete process
  • Follow-up to arrange availability