About Zero to 1
Company: Zero to 1
Industry: Technology consulting and AI solutions
Locations: New York, United States; Bangalore, India; The Hague, Netherlands
Company Size: 11-50 Employees
What They Do: Technology
Website: https://www.zeroto1.ai/
Q&A with Bruno Dupont, Co-Founder & Head of Data, Zero to 1
Q: What made the Community Impact Initiative the right fit for your startup?
A: We first learned about the Community Impact Initiative after connecting with D'Amore-McKim at a career event. As we looked at the challenges we were tackling, it became clear the program was a great fit. As a startup building AI-powered, client-facing tools, we need sharp thinking, speed, and actionable insights. The student consulting team brought exactly that, delivering meaningful recommendations and real value from day one.
Q: What projects did students work on?
A: We asked student teams to evaluate the performance of our AI analytics agent against human analysis. Using the same dataset and business questions, each team took a different approach—some used advanced analytics tools, others leveraged ChatGPT, and another worked in Excel. This allowed us to compare how people and AI interpret data, solve analytical problems, and generate insights. Their findings helped us identify where the AI excelled, where human judgment made the biggest difference, and how to refine the agent to deliver greater value in real-world applications.
Q: How does the Community Impact Initiative differ from a traditional internship model?
A: What sets this experience apart is the level of independence and ownership students take on. This isn't a traditional internship model where you're managing day-to-day tasks. Instead, in a Community Impact Initiative, you define the problem, and they take ownership of delivering polished, professional work with a level of rigor and independence that feels much closer to working with an external consulting team.
It felt less like managing interns and more like collaborating with a consulting team. I was impressed by their commitment and professionalism. They handled complex workstreams, applied strong analytical rigor, and operated at a sophisticated level of expertise.
Flexibility is another major advantage. Whether you need a single highly capable contributor or a team tackling a complex project, the model adapts to your needs. For us, working with a team meant diverse perspectives and deeper analysis, which elevated the final output.
Q: What tangible value did the students deliver?
A: The students delivered insights that had an immediate impact on our product. They showed us where our AI was performing well, where human judgment still had the advantage, and where we could refine our models to better reflect real-world decision-making.
They also uncovered patterns and connections we hadn't considered, giving us new ways to strengthen the product. Their response to intentionally embedded anomalies helped us improve how our AI detects and interprets unusual data.
Beyond the specific findings, the project gave us something equally valuable: a structured, outside perspective that challenged our assumptions and strengthened our testing process. That external feedback loop has since become a core part of how we evaluate and improve our tools.
Q: Would you recommend this model to other employers?
A: For any organization with project-based work, especially in fast-moving, technical environments, this is an incredibly effective way to access top-tier talent while advancing meaningful business priorities. We gained valuable insights for our product development and established a repeatable feedback loop that we continue to use today.
We absolutely recommend this model, and see potential for this to evolve into a broader talent pipeline as we continue to grow.
