AI Foundry & Azure OpenAI
Model selection, grounding on your data, evaluation harnesses and deployment patterns that hold up in production. Provisioned throughput where latency matters, serverless where it does not.
Practice 02
Microsoft is shipping AI into every surface you already run. We make that AI useful, identity-governed and cost-visible, delivered by people who have run enterprise Azure for decades, not prompt merchants with a demo.
Model selection, grounding on your data, evaluation harnesses and deployment patterns that hold up in production. Provisioned throughput where latency matters, serverless where it does not.
Copilot readiness, Copilot Studio agents and Graph connectors that respect your permission model. An agent that can see what a user cannot is a breach, not a feature.
Entra-backed access, Purview data boundaries, private networking and content filters. AI lands inside the controls your security team already trusts.
Token budgets, per-workload metering and FinOps reporting from day one. The second-most-common way AI projects die is an invoice nobody predicted. The first is a pilot nobody governed.
Your tenant, your keys, your record. Inference runs where your data residency and classification allow. Prompts, responses and evaluations stay in your observability stack.
Evaluation before enthusiasm. Every workload gets an eval harness before it gets a stakeholder demo. If we cannot measure it, we do not ship it.
A person closes the loop. Agents draft, retrieve and recommend. Decisions that matter route to a named human with the evidence attached, and the record survives.
Bring us a workload, a Copilot sprawl or an AI pilot that needs to survive production review.
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