Architecture That Takes AI from Pilot to Production
The gap between a working notebook and a production AI system is architecture. We design Azure-native solutions that scale, stay secure, and don't break the budget — so your models actually ship.
The Challenge
AI prototypes work in isolation but fail in production. Without deliberate architecture — covering data pipelines, model serving, security boundaries, and cost controls — teams hit walls at scale.
Our Approach
Requirements Analysis
Map functional requirements, data sources, latency targets, compliance needs, and budget constraints.
Architecture Design
Design the end-to-end Azure architecture — compute, storage, networking, AI services, and integration patterns.
Security & Governance Layer
Define identity, access controls, data encryption, and policy guardrails aligned with your compliance framework.
Design Review & Handoff
Peer-reviewed architecture document with deployment guides, cost projections, and operational runbooks.
What You Get
- Azure architecture blueprint (diagrams + specifications)
- Security and compliance design document
- Cost model and optimisation recommendations
- Deployment guide and IaC templates
- Operational runbook for day-2 operations
Platform Connection
Architectures are designed to integrate with CloudGenie for ongoing governance, ensuring the environment stays compliant after deployment.