Cloud Factory Solutions Consulting

Secure. Intelligent. Cloud-native.

We turn complex technology into secure, scalable business platforms.

Cloud Factory Solutions is a consulting practice working at the intersection of Cybersecurity, AI Infrastructure, and Cloud. We design architectures that survive production, and we hand them over to the teams who have to run them.

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  • Cybersecurity
  • AI Infrastructure
  • Cloud

One architecture. Security built in. Intelligence ready to scale.

  • Designed once

    One target architecture, governed consistently across accounts, regions, and teams.

  • Enforced by default

    Controls ship with the platform as code, so they hold when delivery speeds up.

  • Ready for AI

    Foundations sized and secured for the compute, data paths, and serving that AI work needs.

Services

Three disciplines, practised as one engineering conversation.

Each pillar stands on its own as an engagement. Together they cover the whole path from control design to a running platform that can carry intelligent workloads.

01

Cybersecurity

Security designed into the platform rather than bolted onto it — so controls are enforceable, auditable, and do not become the reason delivery slows down.

  • Security architecture and strategy

    Target-state security architecture, control mapping, and a sequenced roadmap tied to the risks your business actually carries.

  • Cloud security posture

    Baseline hardening, drift detection, and continuous posture management across every account and subscription — not just the ones under review.

  • Identity and access management

    Identity treated as the primary control plane: federation, least privilege, entitlement review, and joiner-mover-leaver automation.

  • Zero Trust

    Segmentation, workload and device identity, and policy enforcement designed on the assumption that no network position grants trust.

  • Vulnerability and exposure management

    Risk-based prioritisation, clear ownership routing, and remediation workflows built to close findings rather than re-report them.

  • Security automation

    Guardrails, policy as code, and automated response so repetitive control work leaves the human queue for good.

  • Governance, risk, and compliance

    Control frameworks mapped once, evidence collected from the systems of record, and audit readiness that does not duplicate engineering effort.

  • Detection and incident readiness

    Telemetry coverage review, detection engineering, runbooks, and response paths that have been exercised before they are needed.

02

AI Infrastructure

The platform layer underneath your models — compute, data paths, serving, and governance — engineered so AI work can move from promising pilot to supportable production system.

  • AI platform architecture

    Reference architecture for training, fine-tuning, and inference, with tenancy and isolation boundaries decided deliberately.

  • GPU and accelerator strategy

    Capacity, scheduling, and placement decisions matched to real workload profiles, latency targets, and budget envelopes.

  • MLOps and LLMOps

    Pipelines, registries, environment promotion, and release paths that treat models, prompts, and datasets as versioned artefacts.

  • Secure model serving and inference

    Inference gateways, tenant isolation, secrets handling, rate control, and input and output safeguards at the boundary.

  • Data and vector pipeline foundations

    Ingestion, transformation, embedding, and retrieval layers with lineage, quality gates, and access control carried end to end.

  • Observability and evaluation

    Tracing, quality and drift evaluation, and feedback loops that make model behaviour measurable instead of anecdotal.

  • AI security and governance

    Threat modelling for AI systems, model and data access policy, usage governance, and a defensible record of decisions.

  • Cost and performance optimisation

    Right-sizing, caching, batching, routing, and precision trade-offs made explicitly rather than discovered in the invoice.

03

Cloud

A deliberate cloud foundation — accounts, networks, delivery, and operations designed to scale without quietly accumulating fragility and cost.

  • Cloud strategy and architecture

    Workload placement, target architecture, and decision records your engineers can defend long after the engagement ends.

  • Migration and modernisation

    Assessment, sequencing, and honest refactor-versus-rehost calls grounded in operational reality rather than ambition.

  • Landing zones and guardrails

    Account structure, network topology, identity boundaries, and preventive controls established before the first workload lands.

  • Infrastructure as code and platform engineering

    Reusable modules, delivery pipelines, and internal platform patterns that remove toil instead of relocating it.

  • Containers and serverless

    Orchestration, event-driven design, and runtime choices matched to what your teams can operate on a bad day.

  • Reliability and observability

    Service level objectives, meaningful health signals, failure-mode analysis, and operational readiness reviews.

  • FinOps

    Cost visibility, allocation, and unit-economics thinking built into engineering practice rather than reported after the fact.

  • Hybrid and multi-cloud enablement

    Connectivity, identity federation, and a consistent operating model across the environments you are genuinely committed to.

Integrated solutions

Three disciplines. One operating platform.

Security is the foundation. Cloud is the platform. AI infrastructure is the intelligence layer. Designed together, each one reinforces the others — because they share the same identity model, the same guardrails, the same delivery pipeline, and the same telemetry.

Shared across all three

  • Identity model
  • Policy guardrails
  • Delivery pipelines
  • Telemetry

  • Intelligence layer

    AI Infrastructure

    Model serving, data and vector pipelines, evaluation, and AI governance — running on the platform beneath it rather than beside it.

  • Platform

    Cloud

    Landing zones, networks, delivery pipelines, and runtime services — the substrate every workload is deployed and operated on.

  • Foundation

    Cybersecurity

    Identity, guardrails, posture, and detection — designed first, so everything built on top inherits the controls instead of negotiating with them.

Approach

A deliberate path from current state to something your team can run.

Four stages, each with work you can see and an output you keep. No stage depends on us staying indefinitely.

  1. Discover

    We map what exists — architecture, identity, data flows, controls, delivery process — and the constraints around it, technical and organisational alike.

    You keep
    Current-state assessment, risk and gap register, prioritised findings.

  2. Design

    We design the target state and the route to it, making trade-offs explicit and writing down why each decision was made.

    You keep
    Target architecture, decision records, control mapping, sequenced roadmap.

  3. Deliver

    We build alongside your engineers — reference implementations, guardrails, automation, and the pipelines that carry them into every environment.

    You keep
    Working implementation, infrastructure and policy as code, runbooks, test evidence.

  4. Evolve

    We harden operations, transfer ownership properly, and leave the platform in a state where the next increment is obvious.

    You keep
    Operational handover, enablement sessions, review cadence, backlog for what comes next.

Why Cloud Factory Solutions

How we work, stated plainly.

These are commitments about method, not claims about results. Judge them during the engagement.

  • Architecture-led thinking

    We start from the system and its constraints, not from a product we already like. Decisions get written down, and revisited when the constraints change.

  • Security by design

    Controls belong in the architecture and the pipeline. Designed that way, security is enforceable rather than aspirational.

  • Automation first

    If a task happens twice, it gets codified. Guardrails, policy, and delivery as code — so the platform holds its shape under pressure.

  • Operational handoff

    An engagement is finished when your team can run, extend, and troubleshoot what was built without calling us.

  • Vendor-neutral recommendations

    We recommend what fits your constraints and your team, and we say plainly when a tool is not the answer to the problem in front of you.

  • Built for production constraints

    Designs account for budget, compliance obligations, legacy systems, and the people who will be on call for the result.

Contact

Let's talk about your next secure cloud or AI initiative.

Whether you are standing up a landing zone, tightening cloud security posture, or building the infrastructure behind an AI product — start with a conversation about constraints and outcomes.

Start a conversation
contact@cloudfactorysolutions.com

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