Revolutionising Intelligence with LLMs, RAG, Agentic AI & Data Lakehouse
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#Data Strategy#Enterprise Data Architecture#Business Transformation#Enterprise Data Warehouse (EDW)#Enterprise Information Management (EIM)#ETL#Data Integration#Teradata
#Strategy#Enterprise Applications Architecture#Digital Transformation#Applications Portfolio Management (APM)#EAaaS
#Data Strategy#AI Strategy#Enterprise Data Architecture#AI Architecture#DPaaS#GenAI Applications#EAaaS#RAG#LLMs & SLMs#Agentic Frameworks
#IT Strategy#EA Strategy#Enterprise Architecture Practice#Digital Transformation#Architecture Review Board (ARB)#Design Authority#EA Governance#EAaaS
#Data & AI Strategy#Data & AI Architecture#Data Lakehouse#Data Integration#Data Governance#Data Engineering#GenAI Apps#APRA Compliance
#Data Strategy#Enterprise Data Architecture#Advanced Analytics#Enterprise Data Warehouse (EDW)#Teradata LDM (TLDM)
#Strategy#Enterprise Applications Architecture#Digital Transformation#Applications Portfolio Management (APM)#EAaaS#Target Operating Model (TOM)
We established a greenfield Data & AI practice within a global healthcare brand, driving digital transformation under CIO sponsorship. We assumed leadership of the domain within the broader digital transformation program.
The mandate was to transform a fragmented legacy landscape into a modern, scalable enterprise data and AI platform that could drive innovation, improve productivity, and support the organisation’s growth strategy.
Built a greenfield Data & AI practice, cutting costs by 25% and accelerating the shift to AI maturity while ensuring trust, compliance, and scalability.
The Challenge
The organisation is a global manufacturing healthcare organisation, operates under a autonomous, federated model with business units in USA, Europe, MEA, APAC & China etc.
Business Challenges:
- Lack of enterprise-wide Data & AI strategy, with initiatives fragmented across silos.
- Limited clarity on AI opportunities, deployment options, and risks.
- Rising costs across the data value chain due to legacy inefficiencies.
- Low trust in AI adoption without clear governance, compliance, and ethical frameworks.
IT Challenges:
- Legacy stack: Dominated by Oracle EBS and siloed data warehouses.
- Scalability gaps: Absence of scalable architecture to support advanced analytics and AI.
- Governance weaknesses: Weak governance around data quality, metadata, and master data management.
- Security and compliance risks: Amid tightening healthcare regulations (GDPR, CCPA, Privacy Act, etc.).
Our Approach
- Strategy & Alignment
- Defined an enterprise-wide Data & AI strategy, aligning it with business growth objectives.
- Partnered with business leaders using an AI Opportunity Radar framework to prioritise AI use cases and create a 3-year roadmap.
- Established AI principles in line with OECD, EU AI Act, and IEEE standards.
- Operating Model Design & Governance
- Created a Data & AI operating model with clear ownership and oversight while integrating trust layers into AI solutions for governance, security, and observability.
- Led governance forums including the Architecture Review Board (ARB) and Design Authority.
- Technology Enablement
- Modernised the stack by migrating legacy systems to a Snowflake enterprise data lakehouse and AI apps platform.
- Deployed Informatica IDMC covering MDM/RDM, cataloguing, governance, data quality, and integration.
- Data & AI Enablement
- Streamlined data pipelines from Salesforce, Oracle, Workday, and other platforms using generative AI and NLP.
- Customised Large Language Models (LLMs) with agentic frameworks (e.g., CrewAI) to accelerate workflows and boost productivity.
- Cybersecurity & Compliance
- Designed a robust cyber strategy aligned with frameworks such as GDPR, CCPA, Privacy Act 1988, NDB, and ACSC.
- Enhanced security postures to safeguard sensitive healthcare data while ensuring compliance.
Outcomes
A major milestone was the shift from fragmented, monolithic systems to the early stages of a post-modern ERP strategy, consolidating into a shared services environment. Together, these outcomes established.
- Successfully executed an AI strategy that supported the transformation agenda.
- Delivered 25% cost reduction across the data value chain through automation and efficiency.
- Modernised legacy stack to a Snowflake enterprise data lakehouse & AI platform.
- Deployed custom LLMs & agentic frameworks to drive innovation and productivity.
- Shifted the organisation’s maturity from BI-driven insights to AI-powered intelligence.
- Established AI governance through ethical, secure, and compliant standards like OECD, EU AI Act & IEEE.
- Positioned the Data & AI practice as a core enabler of the organisation’s growth strategy.
Program Artefacts
Program Technology Stack
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Customer Testimonial
Before, we were marketing in the dark. Now, we know who our customers are, what they want, and how to speak to them. The 360° view has not only increased our revenue but also strengthened our customer relationships.
Sarah Langston, VP of Marketing, NovaRetail Inc.
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