
Written By: Allen Kopelman
Allen Kopelman is the CEO of Nationwide Payment Systems and host of B2B Vault | The Biz to Biz Podcast.
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With federal funding cuts hitting nonprofits hard and competition for private grants at
an all-time high, finding the right funding has never been more difficult — or more
urgent. In this episode of B2B Vault, Allen Kopleman sits down with Luke Keller, serial
entrepreneur and nonprofit founder, to talk about how his platform Match Grant is using
AI and IRS 990 data to transform the way nonprofits discover and win grant funding.
Luke Keller didn’t set out to build a software company. He and his wife founded a
nonprofit about 13 years ago focused on refugee resettlement. When he stepped back
in as interim director four years ago, things were going well — programs were growing,
federal grants were coming in, and a professional grant writer was on staff.
Then, in what Luke describes apolitically as getting “DOGEd,” three out of four
funding sources disappeared overnight. It was a wake-up call — not just for his
organization, but for the entire nonprofit sector. Thousands of organizations that had
relied on federal funding for decades suddenly found themselves competing for the
same pool of private and foundation grants.
NPR — funded almost entirely by the federal government for 50 to 60 years — lost
all of its federal funding and is now competing for private grants alongside small
nonprofits like ours.
— Luke Keller, Founder of Match Grant
The competition spike is real. Large organizations with entire floors of development
staff and grant writers are now fishing in the same pond as scrappy sub-million-dollar
nonprofits. For context: Allen noted that Broward County, Florida alone has between
8,000 and 10,000 nonprofits — not counting religious organizations or schools. Multiply
that nationally and the scale of the challenge becomes clear.
When Luke went looking for software to help find better-fit grant opportunities, he
found the market lacking. The existing solutions had two major problems: they were
expensive (often $8,000–$10,000 per year) and they weren’t meaningfully leveraging AI.
Most platforms delivered static lists of foundations without the intelligence needed to
identify which ones were actually relevant — leaving small nonprofits with enormous
research workloads and no clear direction.
That gap led Luke to build Match Grant — a platform purpose-built to solve the
matching and management problem at a price point nonprofits can actually afford.
Per year — vs. $8–10K for competitors
Every nonprofit and foundation in the United States (with the exception of faith-
based organizations) is required to file a Form 990 with the IRS annually. For
foundations, these filings are public record and contain a goldmine of information: who
they gave money to, the purpose of each grant, and how much was awarded.
Match Grant pulls in this 990 data going back decades — every time the IRS
releases new filings — and layers AI on top of it to extract insights that would take a
human researcher weeks to compile manually.
Track every application, deadline, and report submission. Integrates with
Google Calendar and Outlook to send reminders so nothing falls through the
cracks.
One of the most valuable — and least known — insights in the episode is the
existence of non-solicitation foundations. These are private foundations that fund
organizations by invitation only. There’s no public application, no website, sometimes no
public presence at all. The only way in is through personal Relationships with board
members.
For most nonprofits, these foundations are essentially invisible. Match Grant makes
them visible by pulling board member information from 990 filings and matching it with
LinkedIn profiles — giving nonprofits a roadmap to start building the right relationships.
As AI continues to improve, Luke expects to layer in additional contact data like email
addresses and phone numbers.
Anyone who has worked in the nonprofit sector knows the grant writing grind. As
Luke put it: if you’ve written one grant, you’ve written 50 — because the core content is
largely the same, with minor variations per application. It’s repetitive, time-consuming,
and often falls on executive directors and program managers already wearing three
other hats.
Match Grant is launching an automated grant writing assistant that changes this
dynamic. The tool will pull from a nonprofit’s boilerplate content, their 990 data, and their
website to pre-fill grant applications — dramatically reducing the time required per
application and improving accuracy. Human review will still be part of the process, but
the heavy lifting gets automated.
Match Grant serves a broad range of users across the grant funding ecosystem:
Allen and Luke touched on something many newer nonprofits overlook: you have to
be grant-ready before you apply. Foundations expect documentation, and showing up
unprepared wastes everyone’s time.
On the reporting side, Luke’s advice is consistent: submit reports even when they’re
not strictly required. If you plan to reapply to a foundation, they will notice whether you
followed up — and it matters. Match Grant’s calendar integrations make sure you never
miss a reporting deadline.
As Allen noted during the episode, Nationwide Payment Systems works directly with
nonprofits to help them process donations and payments. Whether it’s setting up
recurring donation systems, making it easy for large donors to give purposefully, or
ensuring the financial infrastructure is in place to receive and track grant
reimbursements — having the right payment processing partner is a key part of
nonprofit operations. You can learn more or book a demo at nps1.com.
Start your free 14-day trial with Match Grant — or reach out to Nationwide
Payment Systems to streamline your donation and payment processing.
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Written By: Allen Kopelman
Allen Kopelman is the CEO of Nationwide Payment Systems and host of B2B Vault | The Biz to Biz Podcast.
The post How AI Is Helping Nonprofits Find Grant Money Faster | B2B Vault appeared first on payment solutions to grow your business.