From Idea to Impact: How a Cross-School Collaboration Brought a Student Startup to Life

One of the most unexpected highlights of my time at Yale SOM has been the opportunity to collaborate across disciplines—not just within the business school, but across the broader Yale ecosystem. This past semester, that kind of collaboration took on a new meaning when I connected with Isha Singh, a master’s student in computer science, through a course that turned into one of the most pivotal experiences of my MBA journey.

This connection started in a graduate-level computer science course, Industrial AI Applications, taught by Professor Xiuye Chen. In the class, students work on building real AI-powered for real business use cases. I wasn’t enrolled in that class, but my classmate Rudy Cordero ’25 was. One day, Rudy announced to members of the SOM class Generative AI and Entrepreneurship, including me, that the computer science cohort was looking for real startup ideas to collaborate with. I had been delving into the strategic and entrepreneurial implications of AI, and I jumped at the chance to pitch my startup, Rise Media. Rise focuses on revolutionizing influencer marketing by combining trend detection with performance-guaranteed campaigns. The mechanism? An AI engine that can identify viral moments across industries and timelines, making success in influencer marketing quantifiable and replicable.

After the pitch, we had a networking session with members of the computer science class. That’s where I connected with Isha. She had a background in social media analysis and was deeply interested in understanding how AI could be applied to fast-moving cultural content. We immediately clicked. She saw the vision, and more importantly, she saw how her technical skills could help bring it to life.

As a result of that connection, Isha and Annie Jiang ’25, another SOM student in the course, decided to collaborate with me for their class project. Based on the product roadmap and initial testing from my work outside of class, we built out a data ingestion pipeline and trend identification model to act as a proof of concept for Rise Media’s AI engine—a critical early step toward validating our product and attracting future investment. Our goal was twofold. We wanted to test whether an AI model could effectively cluster short-form videos into meaningful trends; we also hoped to compare the performance of trend-identified videos against industry benchmarks.

The results were promising. Our early models were able to correctly identify emerging content patterns with 92% accuracy, and the trends we surfaced outperformed videos in the same industry and timeframe by over 326%. Our investigation gave us both the data and the confidence we needed to take the next step forward—and showed that this wasn’t just a conceptual idea, but something technically and commercially viable.

The structure of the course played a huge role in helping us get to where we did. Professor Chen created space for true cross-disciplinary collaboration, where I was able to bring in the business perspective: defining product-market fit, mapping the use cases for the insights we wanted to deliver, and sense-checking whether proposed solutions aligned with real market needs. On the other side, Isha brought deep technical expertise: helping us understand the feasibility of different paths, weighing trade-offs between approaches, and translating complex AI concepts in a way that made them accessible and actionable. That mutual learning—grounded in both business and engineering—was what allowed us to build something real.

For me, this was a transformative experience. I’ve spent the last four years working in the creator economy, managing talent and running influencer campaigns. But this was the first time I had the chance to build technology from the ground up. It was an entirely new muscle.

I learned how to manage a team with more technical experience than I had, how to translate business strategy into product requirements, and—most importantly—how to pivot when things didn’t work the way we expected. There were moments when the data didn’t cluster neatly, when the model needed refinement, and when we had to go back to the drawing board. But those were the moments when I learned the most—how to research, troubleshoot, and iterate with purpose. Working with Isha and the entire class also brought me closer to the broader Yale community and showed me what true interdisciplinary collaboration looks like.

Professionally, this experience has been invaluable. We now have a functional proof of concept that we can show to potential investors, and it’s laid the foundation for the larger AI engine we’re now building. It’s also helped me sharpen my storytelling around the product, communicating its value to brands, creators, and other stakeholders.

I came to SOM to grow as a founder. This project—and the people I met along the way — helped me do exactly that. Our collaboration reinforced one of the biggest reasons I chose this school: the culture of open-mindedness, curiosity, and collaboration. In a world where innovation increasingly lives at the intersection of business and technology, this experience made me feel like I was exactly where I needed to be.

We’re actively expanding our team and looking for collaborators who are excited about the intersection of AI, social media, and culture. If you have a background in AI engineering, social media analytics, or digital marketing strategy, and you’re eager to build something meaningful, please follow our journey or connect with me on LinkedIn.