WORK IN PROGRESS

Building AI governance and scalable content systems for a global retail data platform

Background

A new frontier in AI-assisted insights demands content ecosystems built for semantic precision at scale.

Mission

I'm partnering across Design, Data Science, and Product to transition services from manual, single-point solutions to scalable, automated systems that maintain brand integrity and accuracy.

CLIENT

dunnhumby

INDUSTRY

Retail SaaS

TEAM

Product Design, Data Science, Engineering, UX Research, Business SMEs

AI governance and semantic guardrails

Partnering with Data Science and Engineering, I define quality guardrails that ensure LLM outputs are technically sound, brand-aligned, and risk-compliant.

My contribution

Defining the "Source of Truth" taxonomies that prevent AI hallucination for high-stake retail data use cases.

Stateful notification systems

Partnering with Product Design Managers to architect a cross-platform notification framework (mobile, web, email) that delivers an ecosystem of action and recovery journeys aligned with the global design system. 

My contribution

Mapping 140+ discrete job stories to temporal triggers, roles, and personalised engagement signals.

Knowledge engineering and taxonomy

Partnering with Data Science and Subject Experts, I develop semantic frameworks, schemas, styling, and taxonomies that allow content to work intelligently across AI-assisted services.

My contribution

Designing glossary entry schemas that allow conversational interfaces to populate real-time data.

Why it matters

I'm collaborating across disciplines to build the foundations that help dunnhumby adopt AI in creative, compliant, and adaptive use cases.

Coherent semantic frameworks and systems are critical in delivering content that is clear, modular, and reusable.

This is infrastructure that helps improve user engagement and comprehension while reducing technical debt.

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