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Data & AI
Order in your data, results from AI.
Most organisations have more data than they use. The problem is rarely a shortage of information, but a shortage of structure and trust. Xylos lays a solid data foundation and maps a workable path to AI that delivers measurable results in your organisation.
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Plenty of data, little to hold on to
You collect data everywhere, while the real question stays unanswered: can you trust your data? And are the decisions you base on it actually right? These are the four challenges we come across most often.
Dashboards that contradict each other
Two reports, two figures. As long as a reliable single source of truth is missing, every dashboard stays a source of debate.
AI ambition without a foundation
The board asks about Copilot and AI agents, while your data foundation is not ready for that yet.
Governance lags behind the ambition
Who owns which data stays vague, while the AI Act sets the bar higher than your current policy can handle.
Pilots that never move on
You experiment with AI, but the proofs of concept rarely reach production. The value stays on the shelf.
Where does your organisation stand with AI?
Before you start a programme, you want to know where you stand today. With the AI Readiness Scan you map that yourself: you answer 18 questions online about strategy, data, people and governance. In five minutes you see your profile, your score per pillar and a quick win for each pillar.
The intelligence layer of your entire organisation
Data & AI is the layer that makes your whole digital environment smarter. We get your data foundation in order and translate it into insights people use every day. From there we map a workable path to AI that your people use in their work, considered and within your governance.
The future of AI is agentic: autonomous agents that carry out tasks independently and drive systems based on your data. We guide that step with proven architectures and human oversight. We combine six building blocks depending on your situation. You choose what you need, we make it all work together.
AI starts with a question that comes before any model: can we trust our data? We help you develop a data vision that supports the business.
We set up governance frameworks, define roles and responsibilities with data owners and stewards, manage master data and give an honest picture of the maturity of your data environment.
The result is a practical foundation on which automation, reporting and AI can build.
We build data architectures on Microsoft Fabric, Databricks or Azure Synapse, tailored to your scale and complexity. We ingest data from applications, cloud workloads, IoT and Microsoft 365.
On top of that we put robust pipelines and storage layers such as Lakehouse, Data Warehouse and OneLake. We monitor data quality and costs across the entire lifecycle.
The result is a reliable source of truth, ready for Power BI, low-code and AI services.
Good reporting gives the right people the right insight at the right moment. We build reporting structures per business domain, set up self-service BI models for key users and automate your data flows, so dashboards keep track of what matters.
Power BI is our standard. We make the most important choices before the first visual exists: which KPIs drive behaviour, and which are merely decoration?
Being ready for AI takes more than having a data warehouse. It requires technology and people to be aligned.
We assess the quality of your Data Foundation. We evaluate your security, privacy and compliance, including the AI Act. And we map your governance and access structures.
Then we identify AI use cases with realistic value, in operations or in customer service. From that analysis we map out a concrete path to AI agents, Copilots or automated flows: solutions that land instead of proofs of concept that stall.
The shift from AI as a tool to AI as an actor is fundamental. Agentic AI means systems in which specialised agents work together and act over longer time horizons, which goes well beyond a chatbot that answers questions.
We determine which processes are ready for this and design the architecture that connects agents securely to your data. From there we grow from a first agent to an orchestrated whole, with governance and human oversight that evolve as agents become more autonomous. To do so, we bring together Azure AI Foundry, Microsoft Copilot Studio and the capabilities of Claude.
Technology without people who can work with it delivers nothing. We train employees in data modelling, report interpretation and the basics of privacy management.
We guide your organisation in the responsible use of AI: what AI can and cannot do, which risks the AI Act covers and what Copilot-driven processes look like in practice.
This runs through our AI literacy programme within Learning Services. With our learning platform OASE and the learning games of PlayForward, that knowledge sticks long after the training.
How a project runs
You start where you stand today. If your data foundation is already in place, we move straight to the use cases. If your reporting still pulls four figures from four sources, that is where we begin. You see results after every step, so you decide yourself how far you go.
1. Maturity scan
We start by mapping your data environment and your ambition with an honest maturity scan.
2. Data foundation and governance
Then we set out the foundation and the governance everything else builds on.
3. Insights and use cases
We translate your data into insights and select the use cases with the most value.
4. AI in production
Next we bring AI into production, tested against your security and the AI Act.
5. Management and adjustment
After delivery we keep managing and adjusting the environment as your ambition grows.
What it delivers
A single source of truth. Reporting and AI draw on the same reliable data. Debates about whose figure is correct disappear.
Decisions based on facts. The right people get the right insight at the right moment.
AI at work. Agents and Copilots become part of your daily operation instead of a proof of concept.
People who can keep up. Through our AI literacy programme, with OASE as the learning platform, your teams work smoothly with AI, also after go-live.
Here's how it works for our customers.
Anthropic partnership: Claude in and alongside Azure
Xylos is an Anthropic partner. That gives us architectural knowledge and implementation experience with Claude, the advanced language model behind Claude.ai and the Claude API among others. It lets us help organisations looking beyond what comes as standard in the Microsoft stack.
Claude excels at complex reasoning, nuanced text processing and reliably following structured instructions, qualities that are crucial in agentic architectures. We design hybrid architectures in which Azure handles the infrastructure and orchestration, while Claude does the cognitive tasks it is strongest at, such as analysing documents or driving agents that require reasoning. We already do this in production at first customer projects.
Which model we deploy, whether that is Azure OpenAI, Copilot or Claude, we choose based on what the challenge requires.
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Ready to get a return from your data?
In an exploratory conversation our experts map your data environment and sketch the first outlines of your path to AI.
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Data & AI never stands alone
A strong intelligence layer builds further on the rest of your environment. Hybrid Cloud provides the infrastructure your data and models sit on. Modern Workplace feeds your data through Microsoft 365 and Teams. Automation and low-code turn your insights into faster processes. Managed Services keeps everything secure and up to date. Xylos brings those layers together.
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Your sector, our expertise
Whatever sector your organisation works in, we speak your language. With deep knowledge of your specific market and challenges, we translate complex technology into solutions that move your business forward.
Working at Xylos
We need your talent and fresh perspective. Together we take on projects that matter, and we experiment with new technologies. We do that every day, with plenty of appetite.