FreeFuse is exploring how the choices users make within interactive content can reflect deeper preferences, risk tolerances, or learning gaps—which could also inform procurement or partnership decisions.

In this project, students will design a procurement decision model that uses:

• User behavior data from FreeFuse content to infer buyer intent or partner alignment
• Generative AI tools (like ChatGPT or Claude) to simulate decision trade-offs (cost vs. risk, speed vs. quality)
• Scoring frameworks to evaluate which supplier or vendor path makes the most sense

The final system should help recommend vendor or fulfillment options based on soft signals (user decisions), AI-driven inference, and traditional procurement factors.

Procurement Decision Model – logic tree or AI-enhanced flow that recommends supplier/partner paths based on strategic criteria

Content-Driven Decision Input Map – how interactive choices from FreeFuse content (e.g., "choose lean vs. agile delivery") translate into procurement needs

Generative AI Prompt System – tested prompts or template for vendor evaluation and scoring

Scenario Presentation – simulate 2–3 content pathways leading to different procurement recommendations, with AI-generated justifications

Executive Summary – one-page brief explaining use case and how FreeFuse could use this to inform partnerships, audits, or product sourcing