Procurement Decision Modeling with Generative AI: Optimizing Partner Selection Through Interactive Content Signals

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.

Pathway Intelligence: Forecasting Interactive Journey Effectiveness on FreeFuse

FreeFuse is an AI-powered platform for building interactive, multi-path digital experiences. As the company expands into personalized content journeys and Agentic AI assistance, there is growing interest in understanding which types of interactive pathways lead to higher engagement and long-term user retention. This project will focus on analyzing and forecasting content journey effectiveness using structural data and behavioral metrics from FreeFuse pathways. In addition to traditional engagement data (e.g., completion rates, drop-offs), students will explore time-to-decision—how long a user takes between choice points—as a signal of content clarity, complexity, and user confidence. Learners will apply data science, predictive modeling, and visualization techniques to identify high-performing pathways, segment engagement styles, and forecast content success based on journey composition and user behavior.

Strategic Partnership Expansion Initiative

FreeFuse is seeking to strategically expand its partnership network and explore new market opportunities. The primary goal of this project is to identify and evaluate potential partnership opportunities that align with FreeFuse's business objectives. By conducting market research and analysis, the team will identify adjacent markets that FreeFuse can expand into, thereby increasing its market presence and reach. Additionally, the project aims to develop a framework for creating brand ambassadors beyond the initial partners, enhancing FreeFuse's brand visibility and influence. This initiative will provide learners with the opportunity to apply their knowledge of market analysis, strategic planning, and partnership development in a real-world context. The project will involve tasks such as researching potential partners, analyzing market trends, and developing strategies for ambassador engagement.

Agentic AI for Smart User Assistance and Automated Onboarding

FreeFuse seeks to develop a lightweight but intelligent onboarding assistant that helps new users navigate and adopt the platform effectively. The AI-powered assistant will greet new users, guide them through setup, and answer commonly asked questions in natural language. The core functionality will include: Conversational onboarding that adjusts based on user behavior (e.g., creator vs. viewer). FAQ automation, enabling the assistant to address typical support questions. Contextual nudges, such as suggesting what to do next or how to get the most out of a feature. The system will be designed using pre-trained NLP tools and rule-based logic to avoid the complexity of building custom AI models. The emphasis will be on flow design, interaction quality, and integration simulation—not deploying advanced machine learning or computer vision.