Turing Challenge

I work as an AI architect on client projects. I come in before the code, while it is still an open question what is worth solving with artificial intelligence and what is not. That means walking an organisation’s processes end to end, pointing at where AI adds real value, and translating that into an architecture and a roadmap the client can actually execute.

AI assessment and strategy

• I lead AI assessments for enterprise clients, with end-to-end analysis of their commercial and operational processes.
• I identify and prioritise candidate use cases: lead scoring, document extraction, proposal generation, predictive maintenance and incident handling.
• The deliverable is not a list of ideas but an order of execution: what gets attacked first, what depends on what, and what has to be fixed in the data before anything starts.

AI solution architecture

• I design architectures built on language models: retrieval-augmented generation (RAG), agents and multi-provider AI gateways.
• I work on Azure AI Foundry and Azure OpenAI, and with open-source models when the case calls for it on cost, latency or data sovereignty.
• The multi-provider gateway is a deliberate decision: it isolates the product from the provider, lets models be compared behind one interface, and stops a pricing or availability change from forcing an integration rewrite.

Presales and integration

• I support the technical side of AI project presales: feasibility, scope and proposal.
• I translate business needs into technical roadmaps, putting first what conditions everything else: where the data comes from, how it integrates with the systems already running, and what can ship in each phase.
• I embed AI components into processes already in production, improving how they run without replacing what already serves.