CloudKraft Consulting Inc. · Enterprise AI Architecture

Your AI programme needs
an architect, not
another vendor.

CloudKraft helps CTOs, CDOs, and Heads of Engineering move from AI experimentation to governed, production-grade systems — with clear architecture decisions, documented trade-offs, and accountability at every layer.

Request a Diagnostic View Engagement Models
What CloudKraft Does
We design governed enterprise AI systems — from diagnostic assessment through to reference architecture and implementation oversight — with no vendor affiliations and no open-ended scope. Every engagement, including ongoing advisory, has a defined deliverable and fee agreed in advance.
Who We Work With
CTOs, CDOs, and Heads of Engineering at regulated enterprises in banking, insurance, healthcare, and public sector — where AI governance is a requirement, not a preference.
Our Approach
Fixed scope. Fixed fee. Clear deliverable. Every engagement produces a specific architectural output. You know what you're buying before work begins.
The Methodology
All engagements are structured around the CloudKraft AI Control Framework™ — a five-layer governance and architecture model built for regulated enterprise AI.
Where Most Enterprise AI Programmes Stall

The failure modes are consistent across industries. Recognising which one applies to your organisation is the first architectural decision.

01 — POC TRAP
Proofs of concept that never reach production
AI demos succeed in isolation and fail at integration. The gap between a working prototype and a governed, scalable production system is always an architecture problem — not a technology one.
02 — GOVERNANCE DEBT
Security and governance designed after the fact
RBAC, audit logging, data lineage, and responsible AI controls cost ten times more to retrofit than to build in. Most organisations discover this during a compliance review, not before one.
03 — VENDOR CAPTURE
Platform lock-in disguised as acceleration
Every AI vendor offers to solve your problem fast. Few disclose the architectural dependencies that make switching painful in eighteen months. Neutral architecture judgment is not something vendors provide.
04 — FRAGMENTED ESTATE
No single owner of the AI architecture
Data, engineering, and AI vendor teams make architectural decisions independently. Without a principal architect holding the thread, the result is a fragmented AI estate nobody can explain or govern.
The CloudKraft AI Control Framework™
A five-layer governance and architecture model for regulated enterprise AI, aligned to OSFI E-23, NIST AI RMF, ISO 42001, and the EU AI Act. Every engagement — diagnostic, blueprint, or advisory — is structured around this framework.
5-Layer Framework
L1
Data Readiness
Data quality, lineage, contracts, and vector store design for AI consumption
Data Contracts Lineage pgvector
L2
Architecture Patterns
RAG design, agent orchestration, integration patterns, and system topology
RAG LangGraph Agents
L3
Governance & Risk
RBAC, audit logging, responsible AI controls, and regulatory compliance
RBAC Audit AI Risk
L4
Operating Model
Team structure, ownership, vendor management, and AI programme governance
Ownership Vendor Mgmt Governance
L5
Integration & Scale
Workflow embedding, observability, cost control, and production hardening
Observability Cost Control Scale
Engagement Models

Three ways to engage CloudKraft — each producing a specific architectural output, on a fixed timeline, at a fixed fee.

T1 Diagnostic
AI Readiness Diagnostic
Current state assessment across all five layers of the CloudKraft AI Control Framework™ — gaps, risks, and a prioritised action plan. The starting point for any serious AI programme.
→
T2 Blueprint
Enterprise AI Architecture Blueprint
Full reference architecture, ADRs, technology decisions, and governance framework — designed for your stack, your regulatory context, and your team.
→
T3 Advisory
Implementation Advisory
Fractional architecture oversight during delivery — weekly reviews, trade-off decisions, governance checkpoints. For teams with builders who need architectural authority.
→
How an Engagement Works

Every CloudKraft engagement follows the same four-step model — from the first conversation to the final handoff.

01
Discovery Call — 30 minutes, no charge
We discuss your current AI landscape, the architectural decision you're trying to make, and whether CloudKraft is the right fit. No sales process. If we're not the right engagement, we'll say so.
30 min · Remote
02
Scoping & Proposal
A written engagement scope, deliverable definition, timeline, and fixed fee — agreed before any work begins. No open-ended statements of work that expand mid-engagement.
1 week
03
Architecture Engagement
Structured delivery of the agreed architectural output, assessed and designed against the CloudKraft AI Control Framework™, with defined stakeholder checkpoints throughout.
3–7 weeks
04
Handoff & Enablement
Final deliverable walkthrough with your technical and leadership teams. Architecture decisions documented. Clean transition to your team or optional continuation as T3 Advisory.
Clean handoff
Principal Architect · Faiz Faruqi
See the reference architectures behind the methodology
CloudKraft's engagement frameworks are grounded in real architecture builds — RAG platforms, agent systems, data intelligence pipelines — documented in detail on faizfaruqi.com.
View Portfolio →
Start Here
Book a 30-minute
discovery call

Tell us where your AI programme is stuck. We'll tell you honestly whether CloudKraft can help — and if so, which engagement makes sense. No obligation before the conversation.

Request a Call View All Services Connect on LinkedIn