Skip to main content

Engineering starts with understanding the problem.

Mateusz Mrugała: Mechanical Engineering graduate, Master's degree in Management, founder of EngiLEAN AI.

I have worked in engineering since 2018. My work has included product design, development of mechanical designs, bringing solutions into series production, automating engineering work and coordinating technical projects.

I have worked in several industries, from automotive and industrial valves to intralogistics. This gave me the opportunity to look at the same problems from different perspectives: as a design engineer, as the person responsible for documentation, as a participant in the production process and as a project coordinator.

Over time I became convinced that many technical problems do not stem from a lack of knowledge or technology. Their cause is often unclear requirements, scattered documentation, unnecessarily complicated processes or a lack of time to put in order what already exists.

These are the problems I decided to focus EngiLEAN AI on.

Why EngiLEAN AI?

I have brought together three areas that may seem distant at first glance: machinery safety, Lean Manufacturing and artificial intelligence.

For me they share a common denominator: they help to reduce errors, organise information and make better technical decisions.

Machinery safety requires an understanding of the design, the hazards and the responsibility for the product. Lean makes waste in processes visible. Automation and local AI tools, in turn, can free engineers from part of their repetitive work.

I do not believe, however, that every problem needs new technology. Sometimes a well-organised process, a corrected document or a simple tool is enough.

What matters most to me is the result

I like solutions whose effects can be checked and measured.

A few examples from my earlier professional work:

  • 7 to 11% less material in castings

    Redesigning industrial gate valves reduced the mass of the castings. At the same time, the reject rate in pressure tests fell from about 3% to below 0.5%.

  • From hours to minutes

    I developed a CAD configurator that shortened the preparation of component documentation: 4 to 6 hours → 15 to 30 minutes. It was used by 8 to 12 engineers.

  • From design to series production

    I took part in the development of heat exchangers for the automotive industry: from concept to series production in about nine months, with a series of 30,000 units.

These experiences taught me that a good solution should not only meet the technical requirements but also prove itself in everyday work.

How I approach my work

  • First understand, then propose.

    Before I propose a change, I want to know what causes the problem, what the constraints are and what really needs to be achieved.

  • I do not complicate what can be simplified.

    Documentation should help people in their work, not exist only to satisfy a formal obligation. The same applies to processes: first remove unnecessary activities, and only then think about automating them.

  • Technology should support responsible decisions.

    I am developing local AI tools that support the preparation of technical documentation and the analysis of work. They are at the development and testing stage. I do not treat them as a substitute for an engineer's knowledge. The results must be verifiable, and the final decision rests with a human.

What I do today

At EngiLEAN AI I concentrate on three directions:

  • Machinery compliance and safety

    I support manufacturers, integrators and importers in reviewing documentation, identifying gaps and organising the compliance process.

  • Lean Manufacturing

    I analyse production processes, look for the sources of waste and propose actions based on data from the shop floor.

  • Research and development

    I build and test local AI tools for working with documentation and for supporting engineers.

I do not want to build a company that promises to solve every problem. I want to grow a business in which technical competence, reliability and practical results matter more than impressive declarations.

Let's talk

If you need a fresh look at machine documentation, want to put a production process in order or are looking for a partner for a technical project, tell me what you are dealing with.

We will check whether, and to what extent, I can help.

Let's talk about your project