This section presents applied simulations focused on preparing content for use in LLM-based systems — particularly Retrieval-Augmented Generation (RAG) workflows.
Each project is designed to demonstrate how UX writing, multilingual adaptation, and structural content design can be optimized for:
These simulations replicate real-world production logic. They are structured, executed, and documented as if built inside an AI product team.
Use cases include:
These projects are not “examples of what I could do”.
They are proof-of-concept deliverables — production-relevant, structurally validated, and technically explainable.
If your team builds AI-integrated experiences and needs someone who can speak both human and machine — this is the work I bring to the table.
RAG Simulation Case 01: UX Portfolio as Vector-Retrievable Content
RAG Simulation Case 02: Multilingual Microcopy for Medical UX & Semantic Retrieval
UX Seuil – Tri symptomatique critique pour parents en situation d’alerte