Growth Signals Engine – Early Indicator Analysis for Partner Performance

Core Path Partners seeks to empower its ecosystem of partner organizations by identifying leading indicators of transformation, growth, or risk across multiple operational and behavioral data points. This project invites students to create a signal detection framework that identifies early markers of success or concern based on patterns in simulated or historical partner performance data. Rather than relying on lagging indicators (e.g., revenue drop), this model would surface real-time soft signals like reduced initiative velocity, engagement drop-offs, or stalled milestone progress—enabling preemptive advisory action.

Unified Intelligence Roll-Up - Designing a Multi-Partner Analytics Dashboard for Core Path Partners

Core Path Partners is a collective initiative designed to bring together partner organizations under a shared framework of growth, innovation, and impact. Each partner brings unique strengths, offerings, and data streams. However, there is currently no unified system to monitor performance, surface collective insights, or generate real-time advisory intelligence across the ecosystem. This project challenges student teams to develop a modular, dynamic analytics dashboard system that enables Core Path Partners to: Understand individual and aggregate partner performance Identify early warning signals or success trends Visualize phase-specific metrics across organizations Support advisory storytelling through data-backed insights

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.

Subscription Churn Prediction and Alert System

FreeFuse is seeking to gain insights into the patterns and timing of customer churn within its subscription offerings. The goal of this project is to analyze existing subscription data to identify key indicators and trends that precede churn events. By understanding these patterns, FreeFuse aims to develop a proactive alert system that can notify the company when users are at risk of discontinuing their subscriptions. This project will allow learners to apply data analysis techniques and predictive modeling skills acquired in the classroom. The tasks will include data cleaning, exploratory data analysis, and the development of a predictive model. The project is designed to be completed by a team of data science students within a single academic program, ensuring a focused approach to the problem.

B2B Creator Acquisition & Partnership Strategy for FreeFuse

FreeFuse is preparing to launch its Agentic AI-powered creation tools—designed not just for solo creators, but also for educators, training providers, creative agencies, and branded content teams. This project challenges student teams to develop a B2B go-to-market strategy that positions FreeFuse as a transformational creative platform for professional creator teams, institutions, and studios. The team will identify ideal B2B creator segments, map out a value-driven acquisition strategy, and propose strategic partnership models that align with FreeFuse’s growth goals.

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 Content Strategist for Interactive Creators

FreeFuse is developing an Agentic AI Creative Assistant that helps content creators by autonomously planning, adjusting, and suggesting creative strategies based on platform data. This project focuses on building just one critical component: the Agentic Planning Framework — a self-contained module that can: Accept a creator’s profile or content goals Analyze example inputs or mock behavior patterns Autonomously break down a content plan into sequential goals/tasks Decide when to revise, stop, or hand off to a human The goal is to simulate how an agent might reason through planning creative output and growth strategies — without needing a full platform UI or live AI deployment.

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.

AI-Powered Sentiment & Emotion Analysis for Interactive Content

FreeFuse, in partnership with Not Your Father's AI and LinkedIn Influencer Oliver Yarbrough, is looking to integrate AI-driven sentiment and emotion analysis to better understand user reactions and emotional responses to interactive video content. This project will involve analyzing real-time user interactions, comments, and reactions to assess which types of content elicit positive engagement, frustration, or drop-off behavior. Students will build a sentiment classification model using NLP techniques, generate insights through behavioral clustering, and create actionable recommendations for optimizing content to improve user retention. By completing this project, learners will develop skills in real-world AI modeling, user behavior prediction, and data storytelling for content strategy optimization.

AI-Powered Community Matchmaking for FreeFuse

FreeFuse is developing an AI-powered matchmaking feature that pairs users based on interests, engagement habits, and expertise to foster creative collaboration within the platform. This project will focus on designing an intuitive and engaging "Find Your Creative Partner" feature that seamlessly integrates AI-driven recommendations into the FreeFuse user experience. Students will conduct user research, create wireframes, and develop a high-fidelity prototype that visualizes the matchmaking system. The goal is to enhance user engagement and streamline collaboration opportunities by providing personalized networking suggestions. By completing this project, learners will gain real-world UX/UI experience, understanding how to design AI-powered features, optimize user flows, and create engaging digital experiences.

Interactive Content Engagement Analytics for FreeFuse

FreeFuse is an interactive content platform looking to analyze user engagement and retention trends to optimize content performance. This project will involve extracting and analyzing platform data to generate insights on how users interact with different types of media. The goal is to identify trends, predict user engagement patterns, and create interactive dashboards for decision-making. By completing this project, learners will gain experience in data-driven decision-making, business intelligence tools, and content analytics, contributing directly to FreeFuse’s marketing and user engagement strategies.

New Feature Development & Testing for FreeFuse

FreeFuse is looking for learners to develop and test a new feature for our interactive media platform. This project will focus on implementing a key feature enhancement, integrating it into our existing tech stack, and ensuring usability through testing. Learners will work on coding, debugging, and refining the feature, while also conducting user feedback testing to optimize functionality. This project provides hands-on exposure to real-world development environments, allowing learners to write production-ready code while working alongside our development team.

SOC-2 Cybersecurity Compliance Assistance with Vanta

FreeFuse is seeking cybersecurity-focused learners to assist in achieving SOC-2 compliance using Vanta, our security compliance automation provider. This project will involve evaluating our security posture, reviewing policies, and assisting with technical implementation to meet compliance standards. Learners will work closely with Wendy Chen, FreeFuse’s Tech Lead, to identify vulnerabilities, document security controls, and ensure alignment with industry best practices. By completing this project, learners will gain hands-on experience in cybersecurity compliance, risk mitigation, and IT security governance, contributing to FreeFuse’s broader security infrastructure.

Smart Self-Service Kiosk – Market Feasibility & Prototyping

This project will focus specifically on the self-service kiosk industry , examining how video-driven decision-making can enhance automation in retail environments such as convenience stores, fast food outlets, and vending machines. Instead of broadly covering multiple industries, students will concentrate on market research and prototyping for a single use case , making the project more structured and feasible within an academic setting. Students will conduct research on industry feasibility, develop a conceptual prototype , and present business insights for implementing an interactive video-based self-service kiosk.

Interactive Video-Controlled Retail Automation System

This project focuses on developing an interactive video system that enhances customer engagement in retail by allowing users to make real-time choices in a FreeFuse-powered interactive media experience. Instead of integrating a full IoT system, this project will simulate product selection and recommendation processes, helping students gain practical experience in interactive media design and decision-based user journeys. By simplifying the project scope, students will develop a robust understanding of interactive video technologies and how they can influence consumer behavior in retail settings.

Strategic Development of AI-Driven Business Insights

The goal of this project is to develop a framework that enables businesses to extract actionable insights from AI-driven analytics. Students will explore how AI models can be leveraged to improve business decision-making, focusing on areas such as customer segmentation, predictive analytics, and data-driven strategy formulation. The project will involve building a prototype dashboard that visualizes AI-generated insights. This project is best suited for computer science, AI, or data analytics students interested in business intelligence and AI-driven decision-making.

AI Model Optimization for Data Refinement

This project focuses on improving data preparation and AI model training techniques to enhance predictive accuracy. The goal is to create a systematic process for refining datasets, ensuring high-quality input for AI models used in various business applications. Students will analyze data pre-processing methods, evaluate how data inconsistencies impact model performance, and develop an optimized approach to dataset curation. This project is best suited for computer science, AI, or data science students with experience in machine learning and data engineering.

AI-Powered Lead Qualification for Sales & Business Development

The objective of this project is to analyze and optimize an AI-driven lead qualification model, ensuring it accurately identifies high-potential leads for sales teams. Students will evaluate different lead-scoring methodologies, refine key input parameters, and assess the AI model’s predictive capabilities. By conducting research and analyzing real-world data, students will provide data-backed recommendations to improve the model’s effectiveness. This project is specifically designed for students in data science, artificial intelligence, or business analytics programs , allowing them to apply classroom knowledge in AI model optimization, data analysis, and performance evaluation. The focus will be on refining the model rather than integrating it into a broader sales automation system, ensuring that the project remains within a single academic discipline.

Interactive Video-Triggered Smart Machine System for Retail Automation

Develop a video-interactive smart machine system that allows users to engage with FreeFuse-powered interactive media (e.g., decision-based video journeys) to control an IoT-connected machine in a retail setting. Users will make real-time choices within an interactive video, and these choices will trigger machine actions such as displaying product recommendations, activating a robotic system, or dispensing a selected product. This project will focus on integrating interactive video decision-making with IoT automation in a controlled environment, demonstrating how media-driven engagement can seamlessly connect digital content with physical systems.

Interactive Content Engagement Strategy Development for FreeFuse

FreeFuse aims to enhance user retention and platform engagement through a data-driven interactive content strategy. This project involves analyzing user behavior to identify engagement trends and improvement opportunities. Interns will develop interactive content prototypes tailored to user preferences and test engagement tactics to optimize user experience. By applying user experience design, data analysis, and content creation, learners will provide actionable recommendations that improve interaction rates and platform effectiveness.

Digital Marketing Strategy

We want students to help us develop a digital marketing strategy to grow and engage our target market. We’d like to know how we can maximize different channels and what will work best for us. The main questions we’d like students to help us answer are the following: How can we create and execute on an inbound marketing strategy to generate leads? What media channels other than social media could we use to bring prospects from unaware to aware and then further coming to our site without paid advertisements? How can we create scrappier ways to generate no-touch sales? How can we message all of this properly?

Customer Support Process Design

As our organization continues to grow, it is important for us to stay up to date with our tools and processes for customer support. This project will work to develop tailor-fit customer support processes and practices. Efforts should include conducting market research in order to determine best practices, and the creation of a customer support process. The main goal of which will be providing product and service information and resolving product and service problems. In addition to this it is essential that we are able to help customers with questions, guiding them to a solution or a supervisor that can further assist. Students will work directly with the Director of Sales & Monetization, providing insight, ideas and feedback.

Sales/Outreach Process Optimization

We would like you to assist in the creation of a custom sales channel. Efforts should include conducting market research in order to determine target market and generate prospects, learning and applying sales techniques and attempting to build a customer base of your own. Students will work directly under the Director of Sales & Monetization, providing insight, ideas and feedback. You will be provided with support, feedback and if successful, future opportunities and recommendations. This project may include, but is not limited to: Documenting our current sales process by interviewing Sales Representatives. Researching competitor’s sales processes and inbound lead strategies. Developing recommended changes for our sales process and strategy. Providing sales scripts for emails and sales calls. The insights that you provide will help our team improve lead generation and increase conversion rates to drive more sales. The final project deliverables will include: A 10-page report detailing your research, recommended solutions, and an implementation plan. A Sales Process outlining the recommended sales process and strategy, including sales scripts for emails and sales calls. A 10-minute presentation on the contents of the report and handbook.