AI infrastructure and platforms

How do you choose the right AI platform? 

AI platforms and foundations 
Your platform decision determines AI ROI for years to come. Whether evaluating Azure AI Foundry, AWS Bedrock, Google Vertex AI, or accelerating deployment with the iO Bonzai platform, the challenge is balancing rapid business value with long-term strategic flexibility. We work with organisations to make platform decisions that align with budget constraints, compliance requirements, and growth objectives while avoiding vendor lock-in. 

• AI platform evaluation — Strategic assessment of platforms against business requirements, budget, and total cost of ownership 

• Model selection and optimisation — Deploy models that deliver measurable business outcomes while controlling operational costs  

• MLOps implementation — Production pipelines that ensure consistent performance and reduce technical risk  

• Cost optimisation — Predictable spending through smart usage strategies and efficiency improvements 

How do you connect your systems to AI? 

Context management and orchestration 
AI delivers business value when it can access your existing technology investments. Connecting CRM customer data, ERP operations, CMS content, and BI insights securely determines adoption success across departments. We design orchestration architectures using Model Context Protocol that enable AI to work with your current systems while maintaining governance and security standards your organisation requires. 

• Context engineering design — Strategic framework for AI to leverage existing business data and processes  

• Agentic orchestration — Coordinated AI systems that work across departments without disrupting workflows  

• Knowledge and data fabric — Unified access to CRM, ERP, CMS, and BI that maximises existing technology ROI  

• RAG implementation — Connect AI to institutional knowledge and business-critical documents 

How do you make your data AI-ready? 

Data-as-a-Product 
AI success depends on data quality and accessibility. Many organisations face challenges with inconsistent data across departments, limiting AI effectiveness and business impact. We transform fragmented data into reliable, AI-ready assets that enable consistent decision-making and measurable outcomes. This approach empowers teams while maintaining data governance standards. 

• Data quality and readiness assessment — Identify which data can drive immediate AI value and where investment is needed  

• Data product design — Structure data to support business objectives and enable cross-departmental AI use 

• MCP server development — Secure connections between business systems and AI applications  

• Data pipeline implementation — Automated data flows that reduce manual effort and improve accuracy 

How do you build AI without Big Tech dependency? 

Non-Big-Tech and EU AI
Strategic independence and regulatory compliance drive many organisations toward alternatives to US hyperscalers. Whether addressing EU AI Act requirements, data sovereignty concerns, or reducing vendor dependency, we design AI systems that align with long-term business strategy. Using open-source models and EU infrastructure, we ensure your AI investments remain flexible and compliant. 

• EU AI Act compliance consulting — Navigate regulatory requirements while maintaining competitive advantage  

• Sovereign AI architecture — EU-hosted solutions that meet data residency and privacy requirements  

• Open-source LLM deployment — Deploy models like Mistral and LLaMA with full control over costs and capabilities 

• AI impact assessment — Strategic evaluation of risks, compliance needs, and business continuity