E. Paul Ejiofor
AI Product Manager. Generative AI products, taken from 0 to 1.
I build AI products from early discovery to real-world launch. The case studies below show how I frame problems, work across teams, and turn ideas into tools people actually use.
Core skills
- AI product strategy
- Problem discovery, AI hypotheses, MVP scoping, roadmaps
- RAG and LLM systems
- Retrieval design, grounding and citations, model evaluation
- Quality and trust
- Regression testing, hallucination guards, feedback loops
- Delivery
- Agile planning, Jira, directing AI coding agents, release management
Case studies
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Echolab
An AI tool that turns messy customer feedback into ranked, evidence-backed A/B test ideas, cutting a 3–4 week analysis cycle to under 24 hours.
85%less time spent reviewing the backlog- Ingest feedback
- Classify and cluster
- Retrieve evidence (RAG)
- Generate hypotheses
- Score and rank
- Push to Jira or Optimizely
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RAG Chatbot for Crew Rostering
An AI documentation assistant that gives airline support teams and clients instant, cited answers from thousands of technical documents.
70%less time searching documentation- Ask in plain language
- Search by meaning
- Retrieve source documents
- Write a cited answer