Operational excellence
We automate your data and AI lifecycles using Infrastructure as Code. Deployments like Datacation's private AI Hub are fully automated for a repeatable process and a standardised, predictable environment.
Cloud, infrastructure & data platform services
Data is a strategic asset, but only the right data and AI foundation turns it into better business outcomes. Without it, it stays untapped potential.
Why it matters
A foundation consists of many components: storage, compute, pipelines, security, and governance. Datacation builds cloud, on-premise and hybrid data platforms where these components work together. With the right infrastructure, we can optimise resource use and costs, accelerate innovation, and ensure your data and AI applications can handle growing workloads.
Your foundation is an environment intentionally designed by Datacation to support evolving goals. As you grow from a core data platform to an AI engine, and finally to an agent-ready architecture, a well-built infrastructure adapts predictably to tomorrow's needs.
What we offer
We automate your data and AI lifecycles using Infrastructure as Code. Deployments like Datacation's private AI Hub are fully automated for a repeatable process and a standardised, predictable environment.
Datacation builds isolated, secure environments for your proprietary data and LLMs, with strict access controls, encryption and clear agreements on how models use your data, so your IP stays under your control.
To prevent runaway cloud costs, Datacation utilises smart auto-scaling, serverless architectures, and intelligent lifecycle policies to optimise storage expenses.
Dashboards in Power BI or Tableau, machine-learning platforms for predictive work, and self-service tooling so business users answer their own questions without creating IT tickets.
Proven in practice
ING Wholesale Banking's Chief Commercial Office reported from many scattered data sources, which made consistent, reliable reporting hard.
In working sessions at ING's Amsterdam headquarters, ING's domain experts and Datacation turned business questions into sketches, then into one simplified data model.
All sources now feed one data structure. More than ten interactive Power BI dashboards built on it are used by ING Wholesale Banking Front Office teams worldwide.
Data modelling across scattered sources, Microsoft Power BI.
What we’ve built
Datacation built an Azure data platform that combines ERP data with weather, traffic and holiday data for a logistics network across the Benelux. By bringing internal and external variables together, the platform is designed to support more reliable deliveries, efficient routes and data- and AI-driven supply chain decisions.
Datacation designed an open-source data platform for a SaaS provider to eliminate vendor lock-in and reclaim data sovereignty. Built on ClickHouse, Dagster, and Cube, the solution provides a future-proof, autonomous architecture that empowers the client to make stronger, independent system design decisions.
What’s in it for you
Data location is a strategic decision, not an afterthought. Whether in an EU cloud, your own tenant or on-premise, we design your architecture so you decide where your data lives and stay in control.
Say goodbye to negotiating over conflicting spreadsheets. We define business logic once in a central data catalogue, so every dashboard and AI model can draw from the same source of truth.
Datacation builds a foundation where pipelines, security and monitoring are set up once, so new AI initiatives can build on what’s already there instead of starting from scratch.
The experts behind it
Paul works with organisations on their data infrastructure, together with our cloud architects for AWS, Azure and Google Cloud. He helps teams choose between cloud, on-premise and hybrid, and builds platforms around what the business needs from its data.
Frequently asked
It depends on your obligations, not on fashion. Cloud (Azure, AWS or GCP) offers flexibility and pay-as-you-go pricing without hardware investment. On-premise, with our partner HPE, gives full control for strict security, sovereignty or legacy requirements. Hybrid combines both: critical data local, variable workloads in the cloud. Our architecture assessment determines your best fit.
To make infrastructure AI-ready, you need meaning, trust, and action. Use a semantic layer to give AI business context. Use catalogues and lineage for traceable, trusted data. Finally, use an abstraction layer and APIs to hide database complexity, letting your AI trigger business actions.
We start by mapping your current landscape: ERP, CRM, databases, files and external applications. Most sources connect through standard connectors or APIs. For older systems without an API, we use database replication or scheduled exports. Your systems keep running as they are while the platform reads from them, so we add sources step by step, starting with the ones your first use cases need.
Cost control starts with visibility. Through our AI Hub, we set up dashboards that show token usage and spend per user or team. On the cloud side, we configure budgets, automated cost alerts and financial dashboards. Unexpected spikes are flagged early, so you can adjust before they add up.
That depends on your starting point and ambition - but our approach is iterative by design. The first tangible results and dashboards arrive early, while the platform grows underneath. You never wait for a big bang.
Tell us what you are working on. We will get back to you and explore together what data and AI can do for you.
