In the past 2 weeks, our team kicked off the first sprint of the fundr-AI-se project! We began by getting to know each other and gaining a deeper understanding of our project stakeholders. Over the next four months, we’ll be working closely with our community partner, Meaningful. They are a non-profit company designing an AI-powered platform to help non-profit organizations streamline their workflows (which are often scattered across multiple tools) into a single integrated platform. Our project aims to enhance Meaningful’s AI capabilities to better support non profit organizations, their members (sponsors, donors, volunteers, executives, etc.), and the community they serve.
We observed interviews and demos between Meaningful and non-profits (Acetech and InspireToUplift), which gave us first-hand insight into the users’ needs. We ended the week with a problem discovery meeting with Raaj (CEO of Meaningful), which solidified our understanding of the problems that non-profits face. As a team, we refined our skills in crafting open ended questions to conduct an effective problem discovery to gather insights into pain points of non-profits.
Our first big challenge was understanding what our stakeholders’ main problems were. As a team of computer science students, we are eager to develop solutions right away without taking a step back to see the bigger picture. By reviewing interviews between Meaningful and various non-profits (Acetech and InspireToUplift), and using empathy design principles to gather insight, we were finally clear on the main issue we wanted to solve: Non-profits struggle with member retention due to the high volume of work required to keep them engaged and lack of funding. If this work volume can be decreased or automated then it would allow non-profits to have more time to grow their organization and help the community. This is what our team has set out to solve. Our process of problem discovery on this project, with a strong focus on empathising with the end user, is a valuable lesson we will carry with us as we work on other projects in the future as we believe it guides us towards building better solutions.
This problem discovery led us to our initial solution. We’re planning to use Agentic AI and MCP servers to create a context-aware AI Email Assistant. This tool will be fully integrated to the Meaningful software, allowing non-profits to draft effective personalized emails to their key relationships.
Another challenge we experienced was being split into two groups: one focused on supporting Meaningful with the development of their platform while the other develops our new AI feature. At first, this division felt like a challenge because we all wanted to work on new cutting edge AI technology. However, we quickly came to see the benefits: the former group developed familiarity with the codebase and became a bridge between the platform and the team working on the new feature. In addition, Meaningful has placed their trust in our team to immediately contribute to the production codebase, which gave us a strong sense of ownership and significantly boosted our confidence as a team.
Overall, the sprint laid a strong foundation for the work ahead as we learnt to balance stakeholder needs whilst building on our own technical skills. We’re excited for the next sprint, where we’ll continue to develop our solution and begin testing with end users!