About us

AI is an IT system and the same rules apply to it as to any other — it has to operate lawfully. The list of requirements is long, but it is also an opportunity to keep control and protect innovation. A person working with AI saves time. An organisation gains when the same effect is repeated across hundreds of cases, to the same standard and with clearly assigned accountability. This is not a harder version of the same thing — it is a different kind of benefit, and you reach for it differently. This is enterprise AI — AI for institutions and businesses. This is what we do. Our advantage is ready SAIE products, the CDF methodology and AI-dedicated implementation services, a committed team and experience working with the data of the largest institutions. The research and development projects we run build an advantage that cannot be bought from a model vendor

I treat AI tools like any other system in an organisation — they are valuable when they work within clear rules. As a lawyer, I look at AI through the lens of accountability and regulation: the AI Act and the Polish Act on artificial intelligence systems are not an obstacle for me but a map showing how to deploy these tools safely and to the client’s benefit. As a management systems auditor, including ISO/IEC 42001, I check every day whether AI does exactly what it promises and whether it leaves evidence behind. I use AI intensively myself — from financial analysis, through monitoring case law, to audit documentation — but the final word always belongs to a person. Good AI does not replace accountability; it shortens the path to a decision

At allclouds.pl we work in an AI First model, in which artificial intelligence supports everyday processes, analysis, document creation and decision-making. Every day we use the SAIE Ecosystem, which brings together the TWIN:DESK workspace, the PROXY:AI model management platform and the CDF methodology and compliance platform. This lets us analyse information faster, automate repetitive tasks, make effective use of the organisation’s knowledge and keep full control over data. We use both commercial models and local models running in our own infrastructure, keeping freedom of technology choice and information security. This is what we call Speed 3.0. Competitive advantage increasingly comes not from access to AI itself, but from the speed and quality with which it is used

When ERP systems were entering the market, the most common arguments against them were “it won’t work here”, “it makes too many mistakes” or “we have our own specifics”. In reality, it was almost always about the same thing — fear of change. Implementation meant that work would become transparent. Yet today nobody questions the case for using ERP. Artificial intelligence is now at a similar stage. It can already give people real help, solve complex tasks and process data sets. In fact, artificial intelligence can do far more today than organisations are able to adapt to their own needs, and it can do so even without human involvement and without having to send data somewhere out into the world. And yet we still seem to hear: “but it makes mistakes”, “we have our own specifics” and the like

As an R&D team, however, we do not wait for resistance to fade naturally — we actively overcome it by creating solutions that are ready to deploy here and now. Through broad R&D work we make the future the present. We do this so that in a few years’ time, asking whether artificial intelligence makes sense in a company will sound as strange as asking today whether it is worth having an ERP

In artificial intelligence, the technology itself is only the beginning. The real challenge is turning the capabilities of AI models into products that an organisation can trust and use at scale. That requires more than a good model — it needs the right architecture, control over data and access, clearly defined accountability and a user experience that makes AI a natural part of everyday work. I see the greatest value at the intersection of product and technology: where a business need meets architecture, regulation and engineering, and an experiment stops being a demonstration and becomes a production solution

The real value of artificial intelligence in business begins where an organisation gains full technological sovereignty. This means a company’s right to choose freely how it works with AI — from which language models we currently use to how and where our data is physically protected. Instead of becoming dependent on a single global provider, we should build flexible environments that allow technology to be changed smoothly and that protect the organisation’s unique know-how. Only this kind of independence guarantees that innovation becomes a safe tool working exactly on our own internal terms

Artificial intelligence becomes a real business tool only when it is properly embedded in the organisation’s infrastructure. AI should form a coherent ecosystem connecting data, knowledge, models, automation and security, rather than a collection of separate tools deployed in one department after another. The organisation must be sure that the whole environment is efficient, scalable, monitored and ready for production. That means choosing the right technology and infrastructure, integrating with existing systems, controlling access to data and ensuring security at every stage of the solution’s operation. A good AI deployment is one that can grow with the organisation while keeping full control over the technology, the data and how it is used