About

Two businesses built and acquired. 30+ enterprise AI deployments. Now helping UK SMEs do this properly.

My job is to help you turn unmanaged, inconsistent AI adoption into a governed workforce capability that improves productivity, reduces operational drag and delivers measurable results without enterprise complexity or consultancy overhead.

2 AI businesses built 17+ years operationalising AI 30+ AI projects delivered UK SMEs only
The founder

I’m Dean.

I help organisations figure out what AI can, and should, do for them, and then make it happen. Over 17 years I have scoped, designed and led more than 30 AI deployments across healthcare, defence, financial services, government and global enterprise. Not pilots or proofs of concept that go nowhere, but working systems that reduce workload, improve outcomes and generate measurable results.

Before this I built and sold two technology businesses. I founded ubisend, a conversational AI platform, scaled it from zero to acquisition in 2022, and before that built and exited a FinTech business in 2014. Building both sides of the table gives a perspective that is genuinely uncommon in consultancy: I understand the commercial reality of running a business where delivery quality, responsiveness and client relationships directly impact revenue, and I understand what it takes to build something that actually works under real operating conditions.

I started dkww because UK SMEs are now dealing with exactly the operational pressures larger organisations faced years ago: staff using AI informally without governance, high-value people buried in repetitive admin and leadership under pressure to improve productivity without endlessly growing headcount. The difference is that SMEs rarely have the internal capability, budget or time to navigate it alone.

My goal with you is to bring the deployment depth, commercial realism and implementation discipline from my background in a way that is practically delivered and designed to build internal capability rather than consultancy dependency.

Dean
Dean
Dean on stage at the Effective Mobile Marketing Awards
Industry speakingEffective Mobile Marketing Awards · London
Dean presenting at an industry event
Operational AI presentationsSME & tech keynote
Dean being interviewed on camera
AI & operations interviewsOn-camera, on AI for SMEs
What I do
AI strategy and business case development
AI workflow and solution design
LLM enablement and implementation
Retrieval Augmented Generation (RAG) systems
Robotic Process Automation (RPA)
AI-driven customer experience and CX platforms
HR and workforce automation and training
Knowledge management and intelligent search
Change management and digital adoption
Stakeholder engagement and C-suite advisory
Integration and workflow automation
Operational transformation and AI adoption
Key skills
AIStrategy
LLMImplementation
RAGSystems
ConversationalAI
RPA andAutomation
SolutionArchitecture
AI AdoptionCoaching
C-SuiteAdvisory
ProjectLeadership
ChangeManagement
StakeholderEngagement
AIGovernance
Career timeline

Operational experience over the last 17+ years.

2024 to now

dkww · Founder

Founder-led AI workforce enablement consultancy focused exclusively on UK SMEs. Practical implementation across recruitment, accountancy, legal and professional services. Workforce enablement, workflow redesign, governance and embedded fractional operating support.

2022 to 2024

ubisend · Head of AI Growth

Led global AI scoping, adoption and delivery following ubisend's acquisition. Responsible for enterprise AI deployments across healthcare, defence, public sector and global enterprise clients including the NHS, BAE Systems, MSD and Johnson & Johnson.

2016 to 2022

ubisend · Founder and CEO

Founded and scaled ubisend from startup to acquisition. Built a conversational AI platform serving clients from UK SMEs to global enterprises. Delivered 30+ AI deployments across regulated, commercially sensitive and high-volume operational environments before the platform was acquired in March 2022.

2014 to 2016

Thrive · CTO

Joined as CTO to bring technical rigour to a team working on behaviour change at scale across governments, NGOs and global brands. Built early experience in how technology influences operational decision-making, which proved directly transferable to AI adoption work.

2010 to 2014

London Stone Trading · Founder and CEO

Founded and scaled a FinTech startup focused on algorithmic and discretionary FX trading. Built proprietary trading infrastructure, automation systems and a structured education programme for retail traders. Acquired 2014.

2002 to 2010

Royal Air Force · Fast Jet Pilot

First in class at RAF College Cranwell. Eight years as a fast jet pilot including operational tours before transitioning to technology and business.

Operational philosophy

The principles behind how dkww operates.

North star

Enable the workforce first. Redesign the workflow second.

Deploying AI into a business without first understanding how the workforce uses it, where the gaps are and what governance is in place produces faster versions of the same problems. The right sequence is always workforce visibility, then workflow improvement, then embedded operational support.

Rule 1

Shadow AI is the real starting point.

In most SMEs, AI adoption has already started informally. Staff are using tools without policy, consistency or oversight. The first job is always to understand what is actually happening before designing anything new.

Rule 2

Build for internal ownership.

Workflows, governance and AI capabilities should ultimately be owned and operated internally by the business. The goal is a team that uses AI confidently and consistently, not a team that depends on an external consultant to function.

Rule 3

Commercial realism over AI enthusiasm.

Not every workflow benefits from AI. Not every team is ready for it. Part of my role is identifying where structured enablement will genuinely improve commercial outcomes and where it will not. Honest assessment before implementation.

Rule 4

Governance is not optional.

Unmanaged AI adoption creates data risk, compliance exposure and inconsistent output. Practical governance, appropriate to SME scale, is a core part of every engagement, not an afterthought bolted on at the end.

I have built two businesses from nothing and delivered AI into some of the most complex operational environments in the world. SMEs don't need a smaller version of enterprise consultancy. They need someone who has done the real work and will do it again for them, at their scale.

Dean
Deployment experience

Enterprise-grade AI experience, applied practically inside SMEs.

The operational patterns below are drawn from real-world AI deployments across regulated, high-volume and commercially sensitive environments. See full engagements.

Recruitment

Unqualified application reduction

Conversational AI pre-screening across 10 to 15 structured topics. 73% reduction in unqualified applications reaching the recruitment team.

Healthcare

NHS patient engagement

AI-driven concierge integrated with appointment automation, treatment guidance and measurable reduction in missed appointments.

Enterprise HR

Workforce AI assistant at scale

HR AI assistant serving 100,000 employees across 75 countries. 43% reduction in central inbox traffic within a three-month proof of concept.

Public sector

Council service automation

High-trust AI deployments handling over 80% of incoming citizen enquiries across housing, council tax, planning and local services.

Hospitality

Multilingual HR enablement

AI HR assistant deployed across four countries in English, Dutch and German. Fewer than 13 escalations to human agents over 12 months.

Recruitment

Candidate pre-screening

High-volume WhatsApp and SMS AI-triage integrated with Reed and Indeed APIs. 30 to 50 screening calls per week eliminated, candidates directly into ATS.

Professional services

Knowledge and pitch base

Searchable institutional knowledge powering faster proposal drafting and more consistent client delivery across distributed teams.

Customer service

Service ticket reduction

AI-driven customer engagement reducing support tickets by 48% within the first 14 days of deployment across a global enterprise client base.

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