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Andy Lawsonandylawson.uk

Independent cloud, EUC & platform consultant

I help organisations regain control of complex cloud, EUC, security and information platforms.

Understanding a platform before changing it is most of the job. I bring more than thirty years of enterprise infrastructure work across cloud and EUC, Microsoft 365, identity and information estates, and I put evidence in front of every decision.

I use AI as an accelerator, not a substitute for judgement. It widens discovery, classification and documentation. Decisions, validation and implementation remain mine.

Useful where environments are messy, delivery is slow, risk is high, and someone senior needs to make sense of the platform, data and dependencies quickly.

Speak to meView CVView featured work
Andy Lawson, independent cloud, EUC and platform consultant
Andy LawsonUK-based | Remote and on-site
  • IT since 1991
  • AWS EUC modernisation
  • Microsoft 365 and Entra
  • Windows 11 WorkSpaces
  • Terraform and automation
  • AI-assisted discovery
  • Information estates
  • Controlled decommissioning
  • Governance and evidence packs

What I help with

01 / 05

One consultancy offer. Five ways in.

Cloud and EUC, Microsoft 365, AI-assisted delivery, messy files and data, and controlled remediation. One senior person across the whole problem.

01

Cloud & EUC modernisation

Enterprise EUC and cloud platform modernisation across AWS, Azure, WorkSpaces, AVD, Intune, Citrix, MECM and Terraform.Best forlegacy EUC estates / cloud desktop migration / platform rebuilds / controlled decommissions / operational clean-up
02

Security, identity and Microsoft 365 governance

Microsoft 365, Entra, MFA, Conditional Access, identity posture, access control, governance and risk reduction.Best forMicrosoft 365 clean-up / identity hardening / AI-ready governance / access and control mapping
03Pillar

AI-assisted discovery and delivery

AI-assisted methods for discovery, documentation, classification, duplicate analysis, dependency mapping, test planning, evidence packs and remediation planning.AI is used to accelerate analysis and delivery. It does not replace judgement, validation or accountability.
04

Platforms, files and data

Help with messy operational data, file structures, SharePoint, OneDrive, Exchange / Outlook, SMB file shares, migration mapping and acquisition clean-up.Best forfile-storage rationalisation / duplicate analysis / folder restructuring / Outlook-held files / SharePoint clean-up / migration planning
05

Platform rescue and controlled decommissioning

Finding what is really connected, what can safely be removed, what must be retained, and how to move from messy inherited systems to governed, supportable platforms.Best forlegacy platforms / stale objects / decommissioning / risk reduction / audit trails / governance reporting

Not sure which?

Most engagements start with a messy environment and one senior conversation.

Speak to me

Featured enterprise engagement

A major UK insurer · Jan 2020 to Jul 2026

AWS EUC modernisation: Windows 11 WorkSpaces built as code, legacy Citrix estate decommissioned

A major UK insurer needed to modernise an AWS EUC estate, replacing a legacy Citrix-on-EC2 developer desktop platform with a Windows 11 AWS WorkSpaces environment.

AI-assisted analysis

AI-assisted methods were used to accelerate discovery and planning during the modernisation and decommissioning phase. Findings, validation and implementation remained under my own experienced engineering judgement.

What I did

  • Built the Terraform codebase for five Windows 11 WorkSpaces environments, including secure dev, test and prod estates connected to a secure data lake.
  • Delivered the supporting management portal stack using ALB, API Gateway, RDS Multi-AZ and EC2 as independent root modules with remote S3 state.
  • Migrated the MECM primary site server cross-account by AMI / snapshot lift-and-shift.
  • Built EC2 Image Builder pipelines for high-spec Windows Server 2022 application hosts.
  • Decommissioned the legacy Citrix / EC2 estate while preserving load-bearing FSx / DFS dependencies.
  • Used AI-assisted methods during the modernisation and decommissioning phase to accelerate estate discovery, dependency mapping, documentation and implementation planning.
100%
Defined in Terraform
80+
High-spec EC2 application hosts
Zero
User-facing downtime

How I work

Read-only first

I start by understanding, not by moving things.

I do not start by writing scripts or moving data. I start by finding out what exists, what depends on what, what is risky, and what needs human sign-off.

  1. 01

    Discover

    Read-only discovery where appropriate. Inventory the environment, data, permissions, platforms, dependencies and exceptions.

  2. 02

    Understand

    Identify what is current, stale, duplicated, risky, business-critical or poorly governed.

  3. 03

    Evidence

    Produce clear findings, evidence packs, migration maps, dependency views and remediation options.

  4. 04

    Agree

    Turn findings into a controlled plan with assumptions, risks, exclusions and sign-off points.

  5. 05

    Deliver

    Execute approved changes using automation, change control, logging, reporting and human-led validation.

Read-only first. Evidence before action. Automation only after the risk is understood.

AI-assisted delivery

AI-assisted delivery, controlled by experience.

I use AI-assisted methods to accelerate discovery, classification, dependency mapping, documentation, test planning, duplicate analysis, evidence pack creation and remediation planning.

The value is not that AI makes the decisions. The value is that more than thirty years of engineering judgement can be applied faster, wider and with better structure.

AI is useful when the environment is too broad, inconsistent or undocumented for manual review alone. It is not a replacement for accountability.

Principles

  • Human-led validation
  • No blind automation
  • Evidence before action
  • Clear assumptions
  • Client sign-off points
  • Safe handling of data
  • Repeatable reporting
  • Controlled remediation

Messy platforms, files and data

The unglamorous work

The work that decides whether a migration actually holds.

Much of the real work in enterprise environments is not glamorous. It is finding old folders, duplicated data, unclear ownership, inconsistent filing structures, legacy access, acquisition leftovers and content stored in the wrong place.

That work matters. It affects migrations, supportability, Copilot readiness, security, cost, user experience and operational risk.

Environments I work across

  • SharePoint
  • OneDrive
  • Microsoft Teams
  • Exchange / Outlook
  • Microsoft 365
  • Entra ID
  • Active Directory
  • AWS
  • Azure
  • Windows Server
  • SMB file shares
  • FSx / DFS
  • legacy file servers
  • ServiceNow
  • Dropbox
  • Google Drive

What you get back

  1. 01Discovery report
  2. 02Duplicate analysis
  3. 03Migration mapping
  4. 04Folder structure review
  5. 05Risk register
  6. 06Evidence pack
  7. 07Remediation plan
  8. 08Governance recommendations
  9. 09Sign-off ready change plan

Writing and analysis

Updated 25 July 2026

Insights.

Practical notes on cloud and EUC platforms, information estates and AI-assisted delivery, written from real enterprise work rather than theory.

Editorial illustration in three parts. On the left, five restrained source estate cards for SharePoint and OneDrive, Teams and Microsoft 365 groups, Exchange and shared mailboxes, Microsoft Entra identities, and SMB and file estates, all feeding one shared source rail. At the centre and dominating the composition, a connected evidence model holding six linked relationships in two columns and three rows: content, identity, ownership, access, retention and dependency, with a full-width band for collection limitations beneath them. On the right, a shared output rail serving four review outputs: finding, question, decision and evidence. A single dashed return path runs from evidence back to the shared source rail, labelled traceable to source.
Information estatesFeatured

Most data-sprawl projects start in the wrong place

Data-sprawl work often begins with a migration tool, a storage report, or a deletion target. The real first task is to connect the information, identities, ownership, access, retention, dependencies, and unknowns that make any later decision defensible.25 July 2026 · 9 min readRead article
Technical assurance

What evidence should exist before a Microsoft 365 control is changed

13 July 2026 · 6 min read

Information estates

Why duplicate deletion is the wrong starting point for file rationalisation

12 July 2026 · 4 min read

View all insights

Experience

Since 1991

A senior background across cloud, EUC and Microsoft platforms.

A senior technical background across enterprise cloud, EUC, Microsoft platforms, identity, virtualisation, data-centre migration, healthcare, insurance, aviation, managed services and independent consultancy.

01

Major UK insurer

Lead AWS Engineer | EUC & Cloud Platform Engineering

2020 to Jul 2026
02

Great Ormond Street Hospital

Senior Consultant

2018 to 2019
03

Thintech Ltd

Senior Consultant

2016 to 2018

Earlier architecture roles across healthcare, aviation, software and service-provider environments.

View CV

CV

Web-safe PDF

The evidence document behind all of this.

Request my current consultancy CV covering cloud, EUC, Microsoft platforms, AI-assisted delivery, automation, information platforms and selected enterprise engagements.

View CV

Speak to me

Available from August 2026

Someone senior to make sense of a complex environment.

Outline the environment, the decision in front of you and any date or risk already in play. Your message comes directly to me.

See how engagements work
Location
UK-based | Remote and on-site
Direct contact
Available after initial contact
Availability
From August 2026
Consultancy, contract and advisory work

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