Discover the process
Stakeholder conversations, current-state workflows, data, pain points and exceptions.
01 / BUSINESS ANALYSIS · PROCESS TRANSFORMATION · AI IMPLEMENTATION
BUSINESS ANALYSIS · PROCESS TRANSFORMATION
Stakeholder conversations, current-state workflows, data, pain points and exceptions.
Clear requirements, business rules, target workflows and the right intervention.
Stakeholder validation, acceptance criteria, UAT scenarios and release readiness.
Testing, guidance, handover and feedback that make the change work in practice.
PROFESSIONAL CASE STUDY
Business / Project Analyst · 2025–2026A real transformation programme.
Delivered with the people who use it.
At University College Dublin, I supported a university-wide transformation of hourly-paid employment processes across HR Operations, Schools and system stakeholders. My work covered business and functional requirements, process analysis, historical data review, UAT, digital workflows, reporting, stakeholder engagement and phased implementation.
Analysed historical workforce and payment data, then worked with Schools, HR Operations and programme leads to capture needs, pain points and exceptions.
Mapped current and target journeys, turning findings into clearer role guidance, website journeys and implementation-ready InfoHub workflows.
Supported UAT, defect retesting and phased go-live; created practical guidance and training to help HR and Schools use the new process.
Delivery support Requirements, workflow definition, testing, go-live support, guidance, FAQs and training material for HR and Schools.
View the full transformation case studyAPPLIED AI IMPLEMENTATION
CrewAI · roles, tool use, sequential workflows and context passed between agents.
Exa · RAG · source-aware research flows and grounded answers.
Pydantic · structured outputs, validation, evaluation and guardrails.
LangChain · MCP · tool calling, API integration and useful system design.
CURRENT DEVELOPMENT
I am developing applied AI and workflow automation capability through independent products and hands-on training—not presenting it as years of client delivery.
Roles, tool use, sequential workflows and context passed between agents.
Search-led research flows, retrieval patterns and source-aware answers.
Structured outputs, validation, evaluation and human checks around model responses.
Tool calling, API integration, context design and the building blocks of useful AI systems.