Maroun EL KADY

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Inside the lab: a working AI use case

This page is a working example of governed RAG/GraphRAG, the same pattern behind the AI transformation work Maroun leads day to day. Every answer the assistant gives is pulled from an approved, source-tracked record rather than invented: a vector search over the underlying content, combined with graph traversal over the structured career record below, so an answer can cite exactly which role, project, or article it came from: nothing invented, nothing assumed.

See how it works

Documents feed a vector index; a separate hand-curated set of entities and relationships feeds the knowledge graph. Both converge into the same retrieval-ready corpus that answers you, and anything it can't yet answer loops back to expand it. Click a node for details.

CV & résuméProjectsWrite-upsArticlesPublished writingReflectionsDirect Q&AStructured factsVerified dataKnowledge graphRelationships & contextVector embeddingsMeaning-based searchIngested & readyHybrid retrievalYouAsking a question

Explore the career graph

Every role, project, skill, and publication in the corpus, hand-curated as a graph, the same one the chat draws on for structured facts. Drag, scroll, and pan to explore: double-click a node to reveal its connections.

Person
Organization
Role
Project
Skill
Certification
Education
Publication
Reflection
Loading graph…

What can you ask?

Ask about specific roles, the projects behind them, skills and certifications, or the articles Maroun has published. Anything outside the approved record gets a plain “I don't have that”, with an offer to connect you with Maroun directly, rather than a guess.

Roles & experience
Projects
Skills & certifications
Published articles
Working style & leadership