Our AI platform services
Platform selection and evaluation
The right platform choice is an architecture decision with long-term consequences. We evaluate Azure AI Foundry, AWS Bedrock, Google Vertex AI and iO Bonzai based on your context: data sovereignty, security requirements and AI roadmap.
MLOps and CI/CD for AI
AI models that are deployed once but never updated will age quickly. We build the MLOps infrastructure that automates model retraining, evaluation and deployment, so your platform stays current without continuous manual overhead.
Infrastructure as Code for AI
Production AI requires infrastructure that is reproducible and auditable. Via Terraform or Bicep, your AI environments are described as code: deployable, traceable and ready for the AI governance requirements ahead.
Open-source and EU-sovereign AI
Not every organisation can or wants to process data through US cloud providers. We evaluate and implement European and open-source LLMs on EU-hosted infrastructure that meets data residency requirements (as we did for Van Dale on Azure AI Foundry).
Bonzai: from rapid pilot to production
Bonzai has been live since spring 2023, with 1,800+ active assistants and 4 million+ requests per month. Model-agnostic and EU-hosted. If your context requires your own cloud infrastructure, we guide the full migration.
Cost optimisation and model governance
AI platforms can become expensive quickly without deliberate choices around caching, model size and routing. We optimise the cost-to-quality ratio, with governance that maintains control over usage and model performance even after go-live.
Let's discuss your AI platform needs
Our approach to AI platforms and foundations
Building a production AI platform is fundamentally different from running a pilot. Our approach centres on three principles: starting from your current reality, treating infrastructure as auditable code, and choosing technology based on fit.
From speed to sustainability
If you want to prove value quickly, Bonzai is the fastest route: live within weeks, model-agnostic, no heavy infrastructure investment upfront. Once the use case is proven and the organisation is ready, we build the production infrastructure that becomes fully yours. At MieleX, this was exactly the path: Bonzai pilots for rapid validation, followed by a bespoke Azure AI Foundry environment.
Infrastructure as auditable code
Manually provisioned AI platforms are a governance risk: configuration drift creeps in and audits become complex. Infrastructure as Code is not an option for us — it's standard, whether we use Bicep, Terraform or CloudFormation. The result: a platform that is reproducibly deployable, records every change and is ready for future AI governance requirements.
Technology-agnostic, not vendor-neutral
We have partnerships with Azure, AWS and Google Cloud, and we also implement Mistral, Llama and EU-hosted models when that's the right fit. Our recommendation is based on what suits your organisation, not on what maximises partner margins. That's the only way to build a long-term relationship.
Why work with iO?
Production AI, not proof-of-concept thinking
We build AI platforms that run in production and last. Bonzai has been operational since spring 2023 and handles more than 4 million requests per month. MieleX and Etex are organisations that take AI infrastructure seriously, and we have helped shape their architecture choices.
Technology-agnostic is not marketing spin
We have partnerships with Azure, AWS and Google Cloud, and we implement open-source and EU-hosted models when that's the better fit. Our recommendation is based on what suits your organisation, not on what maximises our partner margins.
From technical architecture to business case
The CTO understands the architecture choices. The CFO wants to know what it costs and delivers. The board expects an AI strategy that aligns with business goals. We help you make the technical choices and build the business case that creates internal support for the investment.
2,000+ experts across infrastructure, governance and AI
AI platform work requires more than cloud engineers. It requires people who understand data architecture, security, governance and the business context in which the platform operates. That combination is what we bring.
