Senior Analytics Leader • PhD • GenAI Systems Builder
I build internal AI copilots that cut onboarding time and reduce operational risk, with answers grounded in your own documentation
Most organisations have valuable knowledge spread across PDFs, SharePoint, Confluence, emails, and tribal know-how.A GenAI knowledge assistant turns that into a searchable, governed system that gives teams accurate answers grounded in your own documents (not generic internet responses).
A typical RAG prototype includes:
Document ingestion (PDFs, docs, web pages, exports)
Embeddings + vector search setup
Retrieval-grounded responses (RAG)
Simple UI or API endpoint (Teams/Slack-ready later)
Logging + safety controls (basic governance)
GenAI knowledge assistants are useful across multiple teams especially where knowledge is scattered across documents.
HR & onboarding: “What’s our policy on annual leave, expenses, or remote working?”
Operations (SOPs): “Summarise the process for handling refunds, cancellations, or incidents.”
Sales enablement: “How do we position product A vs B, and what are the key differentiators?”
Customer support: “How do I troubleshoot issue Z, and which steps should I follow?”
AI revenue automation (EngageIQ)
Built an automated personalisation and campaign intelligence pipeline (AWS, analytics + automation).Analytics & insight platforms
Designed KPI pipelines and dashboards that support stakeholder decision-making.ML / GenAI architectures
Prototypes covering RAG, deployment patterns, monitoring, and governance.
I’m a UK-based analytics leader working across advanced analytics, machine learning, and decision intelligence. I hold a PhD in data science-related engineering and have 10+ years of experience shipping end-to-end analytics systems.Outside of my core role, I build selective independent prototypes and systems, mainly focused on GenAI assistants, automation, and data platforms.