Allostasis/Services/Track 01 — Foundations/F.03
F.03 · FOUNDATIONS

AI-Ready
Architecture
Review.

A structured, candid assessment of whether your Azure environment can carry the AI, data and cloud workloads about to land on it — with a prioritised remediation plan you can actually act on.

ServiceF.03 — AI-Ready Architecture Review
TrackFoundations
Typical scope2–4 weeks
EngagementSenior solution architect-led
FrameworksMicrosoft Cloud Adoption Framework · Well-Architected · AI workloads

Why this matters

The architecture you have was not designed for what comes next.

Most mid-market Azure environments grew project by project. There's no landing zone, no governance baseline, and no shared model for networking, identity or cost. AI and data workloads are about to land on it anyway.

We run a structured architecture review against the Cloud Adoption Framework and the Well-Architected pillars — sized for AI, data and Copilot workloads — and produce a prioritised remediation plan, not a thousand-page document.

What it includes

Six work-streams, scoped to your environment.

01

Landing zone assessment

Subscription topology, management groups, and naming/tagging assessed against CAF.

02

Network & connectivity

Hub-and-spoke design, segmentation, private endpoints and DNS reviewed for AI workload patterns.

03

Identity & security posture

RBAC, managed identities, key management and Defender for Cloud reviewed against Zero Trust.

04

Data & AI services

Storage, Fabric, Azure OpenAI, AI Search and AI Foundry placement reviewed against Well-Architected.

05

FinOps & cost instrumentation

Tagging, reservations, budget alerts and chargeback reviewed against the cost reality of AI workloads — not against last year's project portfolio.

06

Prioritised remediation plan

Findings ranked by exposure, effort and AI-readiness impact — with a sequenced remediation plan.

Engagement sequence

How an architecture review runs.

STEP 01 · WEEK 1

Extract & map

Tenant configuration, network, identity and resources extracted and mapped.

→ Current-state architecture
STEP 02 · WEEK 2

Assess

Estate assessed against CAF, Well-Architected and AI workload reference patterns.

→ Findings against framework
STEP 03 · WEEK 3

Prioritise

Findings ranked by AI-readiness impact, exposure and remediation effort.

→ Prioritised findings
STEP 04 · WEEK 4

Recommend

Target architecture, remediation plan and engagement-shape recommendations presented to leadership.

→ Readiness report & plan

Outcomes

What you have at the end.

HONEST

A current-state you can defend.

An architecture document grounded in what you actually have — not what someone hoped you had.

PRIORITISED

Findings ranked by AI-readiness impact.

Not a thousand-page deliverable — a list ordered by what stops AI workloads landing safely.

DECISIONABLE

A target architecture and a sequenced plan.

A leadership-ready view of what to fix, in what order, with what scope.

Other foundations services

What sits alongside.

The next step

Find out whether the architecture can carry what's coming.

Forty-five minutes with a senior architect. We'll ask about your Azure environment, your AI ambitions and your governance reality — and tell you honestly where to start.