Meet Will Schrepferman: a 24-year-old who’s been fundraising for more than half his life.
Will raised his first dollar at age 13 and has spent his entire career around philanthropy and mission-driven organizations. After studying data science at Harvard and working on a startup serving nonprofits, he founded DonorAtlas—the first prospect research tool built from the ground up with AI.
So what makes DonorAtlas different?
Three core innovations:
DonorAtlas is built on a philosophy of transparency and responsible AI use.
First, DonorAtlas pulls data from the entire internet—everything that’s publicly available—rather than a limited set of databases.
Second, everything has a citation. No black box numbers, no unexplained estimates. Every data point links back to its source, which any researcher knows is critical for verification.
Third, the data stays dynamic and up-to-date. Instead of static records sitting in a database for years, DonorAtlas continuously refreshes information and can be corrected when users flag inaccuracies.
How AI actually works in donor research
Will is quick to clarify that DonorAtlas doesn’t use generative AI to write grant proposals or donor outreach. Instead, AI automates specific research tasks: matching profiles across multiple websites, summarizing complex information into digestible formats, and enabling natural language searches.
Imagine typing into a search bar: “Show me donors in New York City who went to Harvard and care about data science education.” That’s how DonorAtlas works—more like Google, less like traditional database queries.
The net worth question
One feature that caught my attention is DonorAtlas’s approach to net worth estimates. Rather than a single mysterious number, the platform provides a range with full context: family foundation assets, real estate holdings, career stage, and other indicators. Every figure comes with bullet points explaining the reasoning behind it—and yes, those are all clickable citations.
Who benefits most from AI-powered research?
Will has worked with hundreds of organizations since launching 18 months ago, from massive institutions to single-person shops. The common thread isn’t size or budget—it’s pain.
If manual research is your bottleneck, if frontline fundraisers go into meetings blind, if you’re reactive rather than proactive, that’s where DonorAtlas delivers value. The tool provides the speed and confidence that organizations need when research capacity can’t keep pace with relationship development.
The human element remains essential
Will emphasizes something crucial: “Fundraising is about people. It’s an essentially human task.” AI handles the data pulling, reading, and summarization—the mechanical tasks that machines do well. But it never replaces human judgment, context, and relationship building.
As we discussed, young development officers who want exhaustive information before even speaking with a donor will learn that approach doesn’t work. It’s relationship first, more information later—always a virtuous cycle.
What’s next: Relationship mapping reimagined
By the time you’re reading this, DonorAtlas will likely have launched enhanced relationship mapping features. This goes beyond traditional connections like shared board service to include:
- Kids attending the same schools
- Neighbors with vacation homes in the same city
- Photos together at events and galas
- A broader definition of meaningful connections
The goal is making it easy to ask: “Who are the 15 people this board member is closest to that have given to climate organizations?” Then providing actionable insights, not just data dumps.
A final note
Will is refreshingly open to feedback, calling user critiques his “favorite kind of calls.” That iterative approach—building, testing, improving—reflects how quickly this space is evolving.
Additional Resources
- DonorAtlas | Solutions for Nonprofits
- Will Schrepferman | Connect on LinkedIn
- CARA Webinar | The Prospect Research Live Challenge: Race, Vote, and Win Better Prospects with AI | 1-2pm ET | Registration