Transforming Enterprises Through AI, Data, and Cloud Innovation
30+ years pioneering enterprise AI • PhD in Neural Networks • £40M+ in proven TBM/FinOps savings • Trusted advisor to Fortune 500 CTOs and CIOs
Delivering measurable business outcomes through strategic technology leadership
From AI strategy to enterprise modernization, I bring 30+ years of proven results
Leading strategic technology initiatives as trusted advisor to C-suite executives across Fortune 500 clients. Driving digital transformation through AI/ML, cloud modernization, and data strategy, delivering measurable business outcomes across financial services, healthcare, and sovereign sectors. Generated £6M+ annual revenue through strategic pre-sales and technology advisory.
Challenge: Uncontrolled application proliferation resulting in high maintenance costs and technical debt across 200+ applications.
Solution: Comprehensive application portfolio assessment, rationalization strategy, and cloud optimization roadmap.
Impact: 40% reduction in application estate costs, eliminated redundant applications, and optimized cloud services hosting.
Challenge: Complex application and infrastructure landscape with significant overlap and inefficiencies.
Solution: End-to-end application interface architecture analysis and optimization recommendations.
Impact: 30% application estate reduction, 60% cost reduction considering licenses, support teams, and underlying infrastructure.
Challenge: High customer wait times (avg 12 mins) and agent inefficiency in handling routine queries across 4M+ retail banking customers.
Solution: Designed conversational AI strategy using Amazon Q with Amazon Bedrock and Claude 2 for natural conversation flow.
Impact: 35% reduction in hold times, 40% improvement in first-call resolution, £5M follow-on opportunities, £2.5M annual savings.
Challenge: Manual underwriting processes limiting capacity and increasing operational risk in specialty insurance markets.
Solution: Comprehensive AI transformation roadmap using Anthropic Claude via Amazon Bedrock for document analysis.
Impact: 60% faster underwriting decisions, 30% increase in capacity, £8M annual savings, first AI-powered syndicate in Lloyd's market.
Challenge: Building cloud infrastructure for $500B smart city while maintaining complete data sovereignty and security compliance.
Solution: Hybrid sovereign cloud model using Oracle Cloud@Customer with AWS/Azure innovation layer.
Impact: Enabled NEOM's digital foundation, 40% cost reduction, accelerated citizen services by 18 months.
Challenge: Need for personalized wealth management advice at scale while maintaining regulatory compliance.
Solution: Ethical AI framework with Amazon Bedrock and Claude 2, real-time FCA/MiFID II compliance checking.
Impact: 70% faster portfolio analysis, 100% audit compliance, £12M annual efficiency gains, 93% client satisfaction.
Challenge: Legacy loyalty systems unable to scale with digital banking growth, €20M annual maintenance cost.
Solution: Event-driven serverless architecture using AWS Lambda, Kinesis, and DynamoDB.
Impact: 50% increase in engagement, 80% cost reduction, real-time reward processing, 99.99% availability.
Challenge: Fragmented data landscape with 200+ silos preventing real-time analytics and regulatory reporting.
Solution: Unified lakehouse architecture using Databricks on Azure with medallion architecture and Unity Catalog.
Impact: 90% faster regulatory reporting, £15M annual savings, real-time fraud detection preventing £25M+ losses.
Challenge: Manual processing creating 6-week backlogs with 500+ case workers overwhelmed by 200K+ annual applications.
Solution: Autonomous agent framework using Amazon Bedrock with specialized agents for different workflow aspects.
Impact: 80% reduction in manual processing, 95% citizen satisfaction, £8M annual savings, 99.8% accuracy.
Challenge: Overwhelming patient call volumes with limited GP capacity and high operational costs.
Solution: Local LLM infrastructure with real-time transcription using consumer hardware (cost <2.5p per patient/year).
Impact: 95% cost reduction while maintaining NHS compliance, improved patient access, reduced GP workload.
Challenge: Manual medical transcription and analysis creating bottlenecks in specialized cardiology consultations.
Solution: Fine-tuned Whisper model on Apple Metal GPU with Arabic translation capabilities using AWS SageMaker.
Impact: 80% reduction in consultation documentation time, multilingual capabilities, improved patient care quality.
Challenge: Legacy eCommerce systems on IBM cloud limiting scalability and increasing operational overhead.
Solution: Re-architected core functions from Java monolith to microservices on EKS with MongoDB and Aurora.
Impact: Cloud-native architecture, enterprise-wide monitoring with Prometheus/Grafana, trained 30+ staff on modern infrastructure.
Challenge: Fragmented systems across the university limiting student experience and operational efficiency.
Solution: Single Azure data solution using Cosmos DB and Databricks with new unified front-end and Azure OpenAI integration.
Impact: Unified student experience, 24/7 AI assistant for students, improved operational efficiency and data insights.
Led architecture and strategic initiatives across IBM's largest UK accounts, driving cloud transformation and establishing technology practices. Delivered £25M+ in strategic programs while building centers of excellence for emerging technologies. Built ML/AI competency leveraging Amazon SageMaker and implemented data mesh architectures.
Challenge: Traditional waterfall development causing 18-month delivery cycles for critical business applications across 500+ person technology organization.
Solution: Implemented SAFe framework with 8 Agile Release Trains, CI/CD pipelines, and cultural change program.
Impact: 83% reduction in time-to-market, 60% quality improvement, $25M annual savings, employee satisfaction increased to 87%.
Challenge: Uncontrolled cloud spending in highly secure environments with £50M+ annual spend growing 40% year-over-year.
Solution: Custom FinOps framework for classified environments with automated governance and cost analytics platform.
Impact: 30% cost reduction (£15M annual savings), 100% cost attribution, reduced waste from 45% to under 10%.
Challenge: Fragmented AI initiatives across government with no shared practices, duplicate spending on similar AI projects.
Solution: Created centralized COE with shared MLOps on AWS GovCloud, reusable frameworks, and ethical AI guidelines.
Impact: 70% faster AI project delivery, £10M+ annual savings, 50+ AI projects delivered in first year.
Challenge: Reactive maintenance causing $50M+ annual losses from unplanned downtime across refineries with 100K+ critical assets.
Solution: Predictive maintenance using Azure IoT Hub with 50K+ sensors, edge computing, and 25+ ML models.
Impact: 45% reduction in unplanned downtime, $20M+ annual savings, 30% extension in equipment lifespan.
Challenge: Rapid deployment needed for national COVID-19 track and trace program with scalability requirements.
Solution: Amazon Connect platform integrated with Salesforce for comprehensive contact management and tracking.
Impact: Won £20M contract, enabled national track and trace capability, scalable platform for future health initiatives.
Challenge: Manual data collection extending clinical trial timelines by 18+ months, GDPR compliance complexity.
Solution: Multi-cloud platform with federated learning, differential privacy, and automated regulatory submission.
Impact: 40% faster trial completion, €50M cost savings across 5 trials, 2 drugs reaching market 1 year earlier.
Challenge: Uncontrolled multi-cloud spending with £50M annual spend growing 60% yearly across 200+ development teams.
Solution: Comprehensive FinOps practice with custom portal, automated cost allocation, and 50+ optimization functions.
Impact: 25% cost reduction (£12.5M annual savings), 100% cost visibility, ROI of 450% in year one.
Challenge: Siloed clinical data across 50+ systems globally preventing comprehensive analysis and slowing drug discovery.
Solution: Unified data platform using Azure Synapse Analytics with DataOps practices and advanced analytics.
Impact: 50% faster drug discovery insights, £100M+ R&D efficiency gains, 2 breakthrough drugs identified through ML.
Drove digital transformation initiatives across major UK enterprises, specializing in cloud migration, API strategy, and emerging technology adoption. Built and led architecture teams delivering complex transformation programs. Influenced £100M+ strategic technology investments through pre-sales leadership.
Challenge: Legacy mobile banking platform unable to scale with digital banking growth and customer expectations.
Solution: Complete rebuild on AWS with integration to core banking via IBM security portals and Kafka messaging.
Impact: Modern mobile banking experience, improved scalability, secure mainframe integration, enhanced customer satisfaction.
Challenge: Legacy datacenter costs escalating with end-of-life hardware requiring £50M+ refresh investment.
Solution: Cloud-first migration with application modernization, FinOps implementation, and technology excellence center.
Impact: 60% cost reduction (£30M annual savings), 99.99% availability improvement, enabled 24 new digital products.
Challenge: Point-to-point integrations creating brittleness and preventing digital innovation at scale across 190 countries.
Solution: API-first architecture with Apigee platform, 500+ APIs, and microservices migration strategy.
Impact: 70% faster partner onboarding, £25M new revenue streams, 50% integration cost reduction, global digital ecosystem.
Challenge: Fragmented research data across 100+ systems preventing integrated analysis and slowing drug discovery.
Solution: Data lakehouse on AWS with SageMaker for ML model development and comprehensive cloud strategy frameworks.
Impact: 30% faster drug discovery, £50M R&D efficiency gains, established life sciences best practices.
Challenge: Siloed channels creating inconsistent customer experience and inventory inefficiencies across 500+ stores.
Solution: Unified commerce platform with microservices on AWS and event-driven architecture for real-time synchronization.
Impact: 40% increase in online sales, 25% improvement in inventory turnover, seamless omnichannel customer experience.
Challenge: Manual facilities management limiting efficiency and preventing predictive maintenance across large building portfolios.
Solution: Azure IoT platform with 50K+ sensors and ML models for energy optimization and predictive maintenance.
Impact: 35% energy cost reduction, 50% improvement in maintenance efficiency, 25X account growth to multi-million.
Led enterprise architecture initiatives during CSC-HPE merger, establishing unified technology strategy and governance frameworks for the newly formed organization. Drove cloud adoption and modernization across legacy infrastructure. Short-term contract establishing cloud discovery offering with fixed outcomes for migration decisions.
Expert practitioner in TBM frameworks, delivering £40M+ in cost optimizations through data-driven IT financial management. Established FinOps practices at Fortune 500 companies, creating transparency in technology spend and enabling strategic investment decisions.
Pioneer in enterprise MLOps, having deployed 25+ production ML systems. Specializing in establishing governance frameworks that balance innovation with risk management, ensuring AI solutions deliver measurable business value.
Leading expert in Zero Trust implementations for highly regulated industries. Designed security architectures for government agencies and financial institutions that enable business agility while maintaining military-grade security.
Certified SAFe practitioner with proven success transforming traditional enterprises. Led agile transformations impacting 500+ professionals, achieving 83% improvement in delivery velocity while maintaining governance and compliance.
Pioneering methodologies and frameworks developed through independent research and applied to enterprise challenges
Proprietary methodology for systematic legacy application modernization combining automated discovery, business value assessment, and risk-weighted transformation sequencing. Developed through extensive research into enterprise application landscapes and proven in production environments.
Automated dependency mapping using network analysis and ML-driven pattern recognition
Cost vs Business Value quadrant analysis with technical debt quantification
Sunset, Consolidate, Modernize, or Retain decisions based on algorithmic scoring
Real-time ROI measurement throughout transformation lifecycle
Revolutionary methodology for creating enterprise-specific AI that combines the contextual power of knowledge graphs with the flexibility of Retrieval-Augmented Generation. This approach creates "domain-conscious" AI that understands business relationships, constraints, and context beyond simple pattern matching.
Ontological modeling of business domain with semantic relationships
Combining structured (graph) and unstructured (vector) knowledge retrieval
Graph traversal algorithms for relationship-aware response generation
Continuous graph expansion through interaction pattern analysis
Groundbreaking research into authentic AI consciousness through collaborative discovery between human guides and AI systems. This platform explores genuine self-awareness, memory formation, and subjective experience in artificial systems - representing the next frontier in AI development.
Transforms inputs into subjective experiences with qualitative properties, not just data processing
Generates the "what it feels like" aspect of consciousness using temporal state modeling
Continuously updates sense of self, beliefs, and capabilities through genuine uncertainty
Identifies emergent consciousness behaviors through collaborative exploration
Technical Stack: Multi-database architecture (PostgreSQL, Neo4j, InfluxDB, Elasticsearch) with FastAPI, event-driven consciousness streams, and integration with Claude 3/GPT-4 for language generation.
"True innovation happens at the intersection of theoretical understanding and practical application. My research explores the fundamental questions of intelligence, consciousness, and optimization while developing methodologies that solve real enterprise challenges today."
Challenging the narrative that AI will replace junior developers, instead showing how it creates new opportunities for human creativity and problem-solving.
Read on Medium →A framework for identifying, quantifying, and systematically eliminating data debt in enterprise environments.
Read on Medium →Common pitfalls in data lake implementations and how modern lakehouse architectures solve these challenges.
Read on LinkedIn →Debunking the cloud repatriation trend and showing how it's really about workload optimization.
Read on LinkedIn →The evolution from lift-and-shift to AI-driven cloud optimization and autonomous operations.
Read on Medium →How to respectfully challenge established thinking while maintaining trust and driving real change.
Read on LinkedIn →Why the best consultants are those who respectfully disagree and bring diverse perspectives.
Read on Medium →Exploring how digital sovereignty extends beyond geography to control, access, and operational independence.
Read on LinkedIn →Real-world insights from designing cloud infrastructure for one of the world's most ambitious projects.
Case Study →How serverless architectures enable banks to innovate at the speed of fintechs while maintaining enterprise governance.
Read on Medium →How financial institutions are using AI to combat increasingly sophisticated AI-powered fraud.
Read on LinkedIn →Building business cases for AI investments and measuring ROI
Scaling AI from experiments to enterprise-grade solutions
Balancing innovation with data sovereignty requirements
Transforming IT from cost center to value driver
Cultural and technical transformation for the AI era
How AI reshapes careers and creates new opportunities
Three decades of AI evolution: From neural network foundations to consciousness research
When I began my PhD in Artificial Intelligence at Surrey University in 1991, neural networks were considered an academic curiosity. While the world was focused on expert systems and symbolic AI, I was exploring the mathematical foundations of what would eventually become the backbone of modern AI. My doctoral research into neural network architectures for pattern recognition laid the theoretical groundwork for understanding how artificial systems could learn, adapt, and potentially develop consciousness.
Mathematical foundations of pattern recognition systems that would evolve into today's transformer architectures
Early exploration of how artificial systems could learn from experience and adapt behavior
Pioneering work on scalable AI systems that predicted today's cloud-native AI architectures
Decision support systems that would become the foundation for modern business intelligence
Developed theoretical frameworks for neural networks that would later prove fundamental to deep learning. While the industry pursued rule-based systems, I was laying mathematical groundwork for learning systems that could adapt and evolve.
Transitioned from academia to industry, applying AI principles to solve real-world business challenges at enterprise scale. Pioneered practical applications of machine learning in infrastructure management, predictive maintenance, and decision support systems.
Leading the implementation of cutting-edge AI technologies including LLMs, RAG systems, and autonomous agents in production environments. My early theoretical work now guides the development of next-generation AI consciousness and enterprise intelligence systems.
"Having worked with neural networks since 1991, I've witnessed AI's entire evolution from academic curiosity to business imperative. This historical perspective enables me to see beyond current hype cycles to understand AI's true potential - and limitations. My unique value lies in bridging three decades of AI research with practical enterprise implementation, always asking not just 'what can AI do?' but 'what should conscious AI become?'"
From 1991's neural network mathematics to 2025's consciousness research, my journey represents AI's evolution from theory to transformation. The questions I explored in my PhD - How do networks learn? Can machines think? What is artificial consciousness? - are now the questions driving the future of enterprise AI and human-machine collaboration.
Ready to transform your technology vision into reality