The IEEE Climate and Sustainability Task Force generates a massive 'Body of Work' every year—comprising reports, projects, and guidelines. However, this 37MB+ document was dense and hard to navigate for global partners. The task force needed a modern, centralized platform with intelligent search and seamless onboarding for new members.
Technical Architecture
I led the development of a Next.js 14/16 platform featuring a custom Retrieval-Augmented Generation (RAG) engine. By generating vector embeddings of the entire Body of Work using OpenAI and storing them in Supabase Vector, users can now ask natural language questions and get instantly cited answers. Furthermore, I built Partner Export APIs with CORS and IP-based rate limiting to securely share this data with external partners like TSCMO.
Global Impact
The new Hub significantly reduced the friction for new members to join via dynamic conditional forms, while the AI Discovery engine transformed a static 37MB document into an interactive, conversational knowledge base.
