Most AI programmes fail before the first prompt is written, on questions nobody thought to ask: can our data be trusted enough to ground on, can our security posture contain what AI is allowed to reach, and do we have anywhere safe for teams to build? Readiness is those three answers, and licences come a distant fourth.
Our readiness assessment scores your estate honestly across data grounding, identity and networking, governance, FinOps and skills, then hands you a prioritised gap list with costs attached. No hundred-page maturity theatre; a working document your platform team can execute.
The platform build that usually follows is Azure AI Foundry done properly: landing-zone aligned, private endpoints and customer-managed keys where residency demands it, Entra identity throughout, quotas and cost controls per team, and evaluation and tracing wired in before the first workload ships. Azure OpenAI models are our default engine, with the platform designed so model choice stays flexible as the market moves.
The result is a place where experimentation is safe and production is boring: dozens of models and agents hosted on one governed platform, instead of sandbox OpenAI resources multiplying on corporate credit cards. That platform is also what our multi-agent and Copilot extensibility work stands on, so readiness investment pays across every AI route you choose.