AI infrastructure and platforms: the foundation your AI runs on
Most AI projects start with the right idea and the right use cases. What determines whether they reach production is the infrastructure underneath: platform choice, data architecture, agent connectivity to business systems, and the compliance requirements that apply. We build that foundation, so your AI scales reliably, securely and in line with regulation from day one.
Platform selection: Azure AI Foundry, AWS Bedrock, Google Vertex AI or iO Bonzai — chosen for your context
From pilot to production: a proven migration path from fast Bonzai prototypes to your governed cloud infrastructure
RAG and context engineering: AI agents that work with your business knowledge, not generic model output
Agentic orchestration: agents that act across your systems and execute governed multi-step workflows
EU AI Act compliance: architecture choices that meet regulatory requirements, built in from the start
Pieter Janssens
CEO
Our AI infrastructure services
Let's discuss your AI infrastructure needs
Our approach to AI infrastructure and platforms
AI infrastructure is not a separate workstream — it's the layer that determines whether AI works reliably in production. That’s why we work on three levels: platform choice and foundation, knowledge engineering and orchestration, and built-in compliance, so each layer contributes to AI that works in production.
Start with the platform that fits your context
There is no universally correct AI platform. The choice depends on your existing cloud landscape, data governance requirements, your team and your timeline. We guide that choice based on your context, from a fast Bonzai pilot to full Azure AI Foundry infrastructure with Infrastructure as Code.
Give your AI agents the right knowledge
RAG goes beyond indexing documents. We design context engineering architectures with smart chunking, hybrid retrieval and automated pipelines from your source systems. Your AI works with current, domain-specific and traceable knowledge, not just what a language model learned during training.
Build compliance in, not on top
EU AI Act requirements don't fit as a layer on top of an existing system. Audit trails, human oversight, bias detection and traceability need to be part of the architecture from the first design decision. We build AI systems where compliance is a design principle, not an afterthought.
Why work with us?
Platform-agnostic, not vendor-dependent
We are a certified partner of Azure, AWS and Google Cloud, and we have our own Bonzai platform. Our recommendations are based on what fits your organisation, not on partner incentives. Etex runs on Azure AI Foundry, Worldline on Google Cloud, each based on their own context.
From experiment to production as a standard pattern
Too many AI projects get stuck in the proof-of-concept phase. We have a proven migration path: start fast with Bonzai, move to your own cloud infrastructure when scale and governance requirements demand it. With Infrastructure as Code and automated pipelines, the move from pilot to production is a manageable step.
AI engineering as a core competence
Our AI Engineering Competence Centre (AIECC) coordinates architecture decisions and knowledge sharing across all AI projects. You're not working with a side AI practice: you're working with a structural AI competence built across 12 campuses and 2,000+ experts.
Proven in production, not presentation-only
At Worldline, we built one of the first production MCP implementations at a major global payment provider. At Brussels Airport, we developed an architectural blueprint for agentic AI orchestration.
AI Pioneer Agency of the Year
We were named AI Pioneer Agency of the Year — and we're just getting started. At iO, we help organisations move beyond AI experimentation and turn it into real, measurable business impact. Ready to make that shift? Let's talk.
