A conversation with Stephen Halasnik of Financing Solutions and Shahar Brukner, CRO of Impala

AI for nonprofit fundraising has changed how organizations acquire donor intelligence, evaluate grant opportunities, and strengthen funder relationships. But more fundraising data does not automatically lead to better fundraising decisions.

Stephen Halasnik, Managing Partner of Financing Solutions (a leader in providing nonprofits with a line of credit), speaks with nonprofit leaders and finance professionals about the real-world challenges that affect fundraising, nonprofit cash flow, funding delays, and working capital planning.

In this conversation, Shahar Brukner, Founder and CRO of Impala, explains why many nonprofits are drowning in information while starving for actionable insights. The challenge is no longer simply obtaining data. It is turning fragmented donor, grant, and relationship information into better fundraising decisions.

For nonprofit leaders, development officers, executive directors, and CFOs, that distinction matters. Having a nonprofit fundraising strategy with stronger fundraising intelligence can improve donor relationships, reduce wasted effort, support nonprofit cash-flow planning, and help organizations better prepare for funding delays and working-capital needs.

Quick Answer: Why Is More Fundraising Data Not Improving Results?

More fundraising data does not automatically improve fundraising because nonprofits need actionable intelligence, not just more information. AI and relationship intelligence can help nonprofits identify better funding opportunities, strengthen donor relationships, and make smarter decisions that support both fundraising growth and financial stability.

In This Episode

  • Why nonprofits are collecting more data but not always raising more money
  • The difference between fundraising data and fundraising intelligence
  • How AI is helping nonprofits consolidate donor and funder information
  • Why relationships still drive philanthropy
  • How existing donors may represent hidden growth opportunities
  • Why board member networks are often underused
  • How better fundraising decisions support nonprofit cash flow and working capital planning

The Nonprofit Data Paradox: More Information, Fewer Insights

Today’s nonprofits collect information from numerous sources, including donor CRM systems, email platforms, event registrations, wealth screening databases, foundation directories, grant applications, board member relationships, and public nonprofit filings.

At first glance, having more data seems beneficial. But in practice, more information often creates more complexity.

Imagine a university with tens of thousands of alumni records. Add foundation data, donor histories, event attendance, volunteer information, and board relationships. Suddenly, the organization has millions of data points but no clear direction on what to do next.

The result is information overload.

Fundraising teams spend enormous amounts of time maintaining databases, cleaning records, and searching for prospects instead of building donor relationships.

As Brukner explains, raw data is not the same thing as direction.

Data Does Not Equal Intelligence

One of the biggest misconceptions in fundraising is believing that collecting more information automatically leads to better outcomes.

Consider a salesperson with access to 10,000 prospects. If they only know names and contact information, but not giving history, interests, relationships, or likelihood to engage, the data provides little value.

The same principle applies to nonprofit fundraising.

Fundraisers need intelligence, not simply data.

Fundraising intelligence answers questions such as:

  • Which foundations are most likely to fund us?
  • Who on our board knows a potential donor?
  • Which funders increase grants over time?
  • What organizations similar to ours are receiving funding?
  • Which relationships should we prioritize first?

Without these answers, data becomes noise.

For nonprofit executive directors and CFOs, this matters beyond fundraising. Better fundraising intelligence can help leaders anticipate funding delays, plan for working capital needs, and determine whether tools such as a nonprofit line of credit may be necessary to manage cash flow between committed funding and actual receipt.

Why Relationship Fundraising Still Drives Philanthropy

Despite advances in AI and fundraising technology, philanthropy remains deeply relationship-driven.

Many nonprofits continue to pursue open Requests for Proposals and grant applications. While these opportunities can occasionally lead to funding, they often produce disappointing results.

According to Impala’s research, only a small percentage of foundations offer open applications. Even fewer provide grants to organizations with whom they have no prior relationship.

This creates a difficult reality: open grants are often the most competitive grants.

Thousands of nonprofits may compete for the same funding opportunity, making success far less likely. A stronger nonprofit fundraising strategy is to cultivate relationships with funders whose interests align with the organization’s work before submitting a proposal.

A small family foundation that gives four or five grants each year may be a better opportunity than competing against thousands of applicants for a national grant program.

The key question becomes: Who already knows someone who can make an introduction?

How AI Is Transforming Fundraising

Artificial intelligence is beginning to change how nonprofits manage fundraising data.

According to Brukner, the best nonprofits are using AI in two primary ways: data consolidation and personalized donor engagement.

1. Data Consolidation

Nonprofits often store information across multiple systems, including CRM platforms, email systems, wealth screening databases, internal notes, collaboration tools, and external fundraising platforms.

Historically, consolidating this information required extensive manual effort.

AI now allows organizations to connect multiple data sources and ask questions in plain language.

For example:

  • Who on our board knows this foundation?
  • Which donors attended our event last year?
  • Which funders support organizations similar to ours?

Instead of spending hours searching databases, fundraisers can receive answers much faster and use that information to guide outreach. Combined with strong fundraising analytics, these tools help nonprofits identify funding opportunities, prioritize donor relationships, and make more informed fundraising decisions.

2. Personalized Donor Engagement

AI also enables more customized donor communications.

Previously, a fundraiser might spend significant time reviewing donor histories before writing an email. Today, AI can help analyze past conversations, giving history, event attendance, previous grants, and organizational updates.

This allows nonprofits to create more personalized communications that strengthen donor relationships.

Personalization at scale may become one of the most important advantages AI offers nonprofits.

The Hidden Opportunity in Existing Donors

Many nonprofits focus heavily on acquiring new donors while overlooking existing relationships.

This may be a costly mistake.

Funders frequently increase grant sizes over time. A foundation might provide $10,000 in year one, $40,000 in year two, and $56,000 in year three.

Yet nonprofits often continue requesting only the original amount because they are unaware of the funder’s giving patterns.

Data intelligence can reveal these opportunities.

Sometimes the fastest path to fundraising growth is not finding new donors. It is strengthening relationships with current supporters.

This also has financial planning implications. More predictable donor and grant growth can help nonprofit CFOs manage nonprofit cash flow, reduce uncertainty, and plan more effectively for working capital needs.

Board Members May Be Your Greatest Untapped Fundraising Asset

Most nonprofit leaders recognize that board members possess valuable networks. However, many organizations fail to activate those networks effectively.

A typical board meeting might include a simple question: Who do you know?

The problem is that successful professionals may know thousands of people. Without specific guidance, board members struggle to identify useful connections.

AI-powered relationship mapping changes this dynamic.

Instead of asking broad questions, organizations can ask:

Do you know anyone connected to this foundation?

Specific requests produce far better results.

Relationship intelligence allows nonprofits to turn board networks into strategic fundraising assets.

Why Open Grant Applications Are Often a Fundraising Trap

One of the most surprising insights from the conversation is Brukner’s view on open grant applications.

Many nonprofits spend significant time searching for Requests for Proposals (RFPs) and open grant opportunities because they represent visible funding opportunities. However, Brukner argues that this approach often produces poor returns.

According to Impala’s research, only a small percentage of foundations offer open applications. Those foundations often receive the highest volume of submissions, making them among the most competitive funding opportunities available.

As a result, nonprofits may spend dozens of hours preparing applications with very low odds of success.

Instead of chasing highly competitive open opportunities, organizations may benefit more from identifying funders with mission alignment and building authentic relationships before requesting funding.

For many nonprofits, relationship-based fundraising can generate significantly stronger long-term results than relying heavily on open applications.

What This Means for Nonprofit Cash Flow and Working Capital

Fundraising decisions do not happen in isolation. They directly affect nonprofit cash flow, budgeting, staffing, and program delivery.

When organizations rely on grants, pledges, or reimbursements, there is often a gap between when money is awarded and when it is received. These funding delays can create pressure even for financially healthy nonprofits.

That is why fundraising intelligence and financial planning should work together.

Nonprofit leaders should ask:

  • Which committed funds are expected, and when?
  • Which funders are likely to renew or increase support?
  • Where could funding delays affect payroll, vendors, or programs?
  • Do we have enough working capital to bridge timing gaps?
  • Would a nonprofit line of credit help protect operations while waiting for funding?

A nonprofit line of credit is not a replacement for fundraising. It is a financial tool that can help organizations manage timing gaps when committed or expected funding has not yet arrived.

For executive directors and CFOs, the goal is not just to raise more money. The goal is to make better decisions, protect operations, and maintain financial stability while advancing the mission.

The Future of Fundraising

AI for nonprofit fundraising helps organizations turn fragmented information into actionable fundraising intelligence. The next phase of AI in fundraising will likely go beyond analysis and automation.

Future nonprofit organizations may build custom AI tools tailored to their specific missions, donor bases, and fundraising strategies.

Imagine AI systems that can:

  • Predict donor behavior
  • Recommend ask amounts
  • Identify board connections automatically
  • Draft personalized outreach
  • Monitor funding trends in real time

As these tools evolve, nonprofits that embrace data intelligence, not merely data collection, will gain a meaningful advantage.

Frequently Asked Questions

Why does more fundraising data not automatically improve fundraising results?

More data often creates information overload. Nonprofits need actionable insights and relationship intelligence, not simply additional information.

How is AI changing nonprofit fundraising?

AI helps nonprofits consolidate data from multiple systems, identify stronger donor opportunities, and personalize donor outreach at scale.

What is relationship intelligence in fundraising?

Relationship intelligence identifies connections between donors, board members, foundations, and organizations so nonprofits can pursue warmer introductions and better-aligned funding opportunities.

Should nonprofits focus on open grant applications?

Open grant applications can be valuable, but they are often highly competitive. Building relationships with aligned funders generally produces better long-term results.

Can AI replace fundraisers?

No. AI can improve efficiency and surface insights, but donor relationships still require human trust, communication, and stewardship.

What is the biggest fundraising opportunity many nonprofits overlook?

Existing donors and funders often represent the greatest growth opportunity because grant amounts and donor commitments may increase over time.

How can better fundraising intelligence support nonprofit cash flow?

Better fundraising intelligence helps nonprofit leaders understand which funds are likely to arrive, when they may arrive, and where funding delays could create working capital pressure.

When should a nonprofit consider a line of credit?

A nonprofit may consider a line of credit when it has strong expected or committed funding but needs to bridge temporary cash flow gaps caused by timing delays, reimbursements, or slow grant payments.

Podcast Transcript

Stephen Halasnik:
Welcome, everyone. My name is Stephen Halasnik, and I’ll be your host for today’s Nonprofit MBA Podcast. I am the co-founder of Financing Solutions, the largest provider in the United States of lines of credit to small nonprofits. If you’re interested in learning about a line of credit for your organization, please visit our website at nonprofitmbapodcast.com.

Today, I’m very excited to be speaking with Shahar Brukner from Impala. Shahar is the Founder and CRO of Impala, which helps nonprofits and foundations turn fragmented grantmaking data into actionable insights. Impala uses AI to make it easier to identify stronger funding opportunities and improve decision-making.

Shahar, welcome to today’s Nonprofit MBA Podcast.

Shahar Brukner:
Thank you, Stephen. Thank you for having me. I’m really excited to be here.

Stephen Halasnik:
Good. Today’s topic is why more fundraising data has not led to better fundraising decisions. Right off the bat, why is that true? To me, more data is always better than less.

Shahar Brukner:
Generally, before starting Impala, I would have agreed with you. But raw data is not the same thing as direction or intelligence.

We are living in a time when the average nonprofit has more data, or can collect more data, in a very easy way. These data points are stored in CRMs, email systems, Slack, platforms like Impala, and other systems of record.

But the more data you have, and the more fragmented it is, the harder it becomes to bring it together into a direction or a decision.

We have worked with dozens of nonprofits of all shapes and sizes, from large universities to local organizations, and I hear this again and again. Think about a huge university that has information about tens of thousands of alumni, funders, events, and what other universities are doing. How do you bring that together into a decision process? It actually becomes harder, not easier.

That is the main issue, but there are solutions.

Stephen Halasnik:
What does Impala do?

Shahar Brukner:
Impala is a data platform specifically for the philanthropic sector.

There is a lot of public data out there, starting with 990s and extending to websites, news, and many other sources. What Impala does is collect all of this public data and put it into a very organized, well-structured platform for everyone in philanthropy.

Our two main customer bases are nonprofits on one hand and grantmakers and philanthropic foundations on the other.

The first thing we did was create these datasets. For example, we scraped every 990 of every nonprofit and every philanthropic foundation since 2014 and packaged that data into profiles for every organization.

Whether you know it or not, your nonprofit already has a profile on Impala. The same is true for foundations.

The special thing about Impala is that it is not just a database. We built a suite of products on top of that data that cater to very specific needs for professionals in the field.

For nonprofits, we have two main products.

The first is what we call ecosystem research. This is the ability to define an entire philanthropic landscape or market that you care about, such as arts and culture in Boston or youth education in the Midwest. We immediately show you every nonprofit working in that area, every philanthropic foundation working in that area, how they work together, who is growing, who is shrinking, and trends over time.

We immediately give you intelligence, not just data, about the market you are operating in.

The second product is our funder prospecting product. The idea is simple. We have seen time and time again that philanthropy runs on relationships.

We rank funders in the United States based on their affinity to you, their capacity to give, and whether they have a relationship to you or to real people connected to you. Then we show you the path to connect.

For example, if I want to connect with the Stephen Foundation, I might see that someone on my board sat with Stephen on another board and may know him. You can think about it a bit like LinkedIn for the nonprofit sector.

Again, it is about taking a huge amount of data that is available and packaging it into a very specific workflow that people actually have. In this case, it is unlocking a relationship that can help them.

Stephen Halasnik:
If you’re a nonprofit, I’m a little unclear how scraping data from other nonprofits’ 990s helps you. Are nonprofits using more of the grantmaker part of the platform?

Shahar Brukner:
We have both sides of the sector. We have profiles for both nonprofits and foundations.

I’ll tell you my personal story. I created Impala after I created my own nonprofit, which gives scholarships to young students. At first, I was asking myself basic questions: Who is giving to what I’m doing? How much? When? And how can I connect with them?

At the time, I didn’t have an answer.

Today, I can go to a profile of any philanthropic foundation in the country and see every grant they have given, who is on their board, how I’m connected to them, who else they are giving to, whether they are giving to organizations like mine, the size of the grants, and whether there are instructions on how to apply.

All of this information is now packaged in an extremely easy and accessible way.

Sometimes I know about a funder that I want to approach, and I can go directly to that profile on Impala. But in many cases, there are more than 200,000 philanthropic foundations in the United States, and I may not know they exist.

So I might use ecosystem research and say I want to see funders of scholarships in New York City. I’ll see every funder. Of course, the top 20 may be the biggest foundations in the country and the ones everybody knows.

But as you start to go down the list, you may suddenly find a family foundation without a website and without much public footprint beyond its 990. It may give to six organizations doing something similar to what you do.

That foundation should immediately be on your radar. Now you not only know that they give, you also know who is on the board and how much they give. The last question is how to connect with them. That is why we created the relationship engine, which shows how you can connect to them through existing funders, board members, advisors, people on your team, and so forth.

We wanted to take the entire prospecting-to-ask workflow and augment it with public data so nonprofits do not have to spend time collecting and analyzing it themselves.

Stephen Halasnik:
What have you noticed nonprofits doing now in the age of AI, especially regarding data? What are some of the best nonprofits doing with AI? How are you using it in your products, and where is it headed?

Shahar Brukner:
It’s a good question. I actually came from a conversation right before this with a large nonprofit that I would consider an expert in how they work with data.

Good nonprofits today understand that AI allows them to do two major things with data.

One is to consolidate it in one place where it is easily queryable and where they can ask whatever questions they want. The second is to use that data in a very customized way with their donors.

Think about a nonprofit that already has established data infrastructure. It probably has a fundraising CRM, sometimes with millions of data points. It might have something like Impala, which gives it information about peers and foundations. It might use a wealth screening tool. It also has email and maybe Slack, where someone may know that the CEO met with a prospective funder yesterday.

Before AI, much of the time was spent maintaining and keeping this data in workable condition. It took a lot of manual work, and it could create real burnout.

AI now allows organizations to connect multiple systems and bring those data points into one place where they can start querying them.

For example, a question like, “I want to speak with Stephen and everyone he knows,” becomes much easier because AI can analyze the data from many different directions.

Consolidation is the first piece. It is not something you do once and finish. It is something you constantly do around specific projects and priorities.

The second piece is customization.

Let’s say I wanted to customize an email to one of my donors. Previously, I would have gone into the CRM, reviewed the history of our calls, internalized it, and then written an email that says something like, “Hi, Stephen. We last connected in April of 2026. It was great seeing you at that event. Since then, we have done A, B, and C.”

But you need the full context. AI can have that full context already. It is much better than humans at connecting data points from different sources.

Outreach can be a game changer because it allows you to customize a message within the context of the organization’s work.

So the two main things good organizations are doing today are consolidation and customization.

If you asked me this question six months from now, I would probably be talking about nonprofits starting to build things on their own, meaning specific AI assets that nonprofits can use for their very specific needs. This is something we are starting to explore at Impala as well, allowing people to use our data to build what they need.

Stephen Halasnik:
So what people have used Impala for in the past is taking their own data out of CRM systems, uploading it, and then combining that with the other data Impala has found. Then they are coming up with a relationship plan or an application plan. Is that accurate?

Shahar Brukner:
It is accurate. I would say that most nonprofits we work with first want to understand what they can do with public data before giving us their own data.

Integrating your own data with an external platform takes time and needs to happen continuously, so people do not jump into it right away. We wanted to create an easier access point.

First, we show people that what they thought they knew about public data, their area, and their donors can actually be expanded much more.

Most people come in and say, “Now I see the world. Now I see my ecosystem. Now I see the relationships I have.”

For most organizations, that alone gives them work for the next year.

If people are more mature in fundraising and have more resources, then their data can flow in as well.

I can give you a real example. We started working with a large university here in the city. We already mapped about 4,000 connections from their board to funders that were not funding them yet. That does not mean every one of those connections will lead to money, but it gives them a lot to work with.

Before starting a big approach, they gave us a list of about 8,000 super alumni, their words, not mine, meaning people who were extremely connected to the university but were not on the board. They were more like quasi-advisors.

Adding those people enriched the platform with 2,000 more connections they could use. So instead of starting with 4,000 connections, they started with 6,000. The results were pretty amazing.

Stephen Halasnik:
Let’s take a scenario where you have a smaller nonprofit that is new to Impala. They come in, and let’s say they stay with you for three years. How do they start using Impala, and three years later, how has their behavior changed?

Shahar Brukner:
Most small nonprofits that come to us in the beginning have two concepts in mind.

One is that there are big funders out there. They know a little about them, but they need to understand what those funders are doing, whether they should be on their radar, and how to connect with them.

The second is that they are looking for open applications, requests for proposals, and opportunities where they can submit their work.

The first thing we do is answer the first need and tell them not to run after the second.

When they come in, we can immediately provide a lot of information about the funders they already care about. We are saving them time right away.

Usually, they create lists of funders, download data, put it into their own systems, build things with it, or act on it. In many cases, once organizations get the data and understand that they have a way in, they pick up the phone, start working on a grant, and three months later, we hear that they received a grant and already returned their investment in Impala.

The second piece is telling them not to go after RFPs.

Open applications, submissions, and requests for proposals, in my opinion as a fundraiser and as someone who runs Impala, can be a trap.

We have information about foundations and know which foundations have open grant applications. Out of all foundations, only a small percentage offer open applications. That means you are already putting a large majority aside.

The foundations that do offer open applications often have the most competitive grant processes because they are open to everyone.

So you are putting yourself into a small pool, but an extremely competitive one. And not every open grant application fits every organization. Some are for arts, some are for youth education, some are for climate change, and so on.

The pool is much smaller than people think.

The problem is that the work is right in front of you. You can write a grant application and submit it, hoping you will get money. But we see that the return on investment for that method is extremely low.

If the foundation does not know you and has never heard of you, and suddenly your application lands on their desk, your chances of receiving money are not zero, but they are extremely low.

This flow can require organizations to waste time, effort, and resources, and the end result is often not very positive.

So we tell them to stop chasing open grant applications and look at relationships they can already use.

Instead of going after very large foundations with huge, open, competitive grant applications, go after a smaller family foundation. Maybe its average grant size is $15,000, and every year it gives to four to six new organizations. That means there may be an open avenue.

The problem is that the foundation may not have a website or an open application. You need to find a way in through a board member, an existing donor, or someone else connected to the foundation.

There is an educational element here. We are pushing nonprofits away from what looks shiny and easy, but often wastes time, and toward something deeper, more authentic, and focused on relationships.

The results are better.

One example that often clicks with nonprofits is the comparison to LinkedIn. When people apply for a job on LinkedIn, they can see how many people have already applied. The chance of sitting at the top of that pile and having someone in HR pick your resume is very low.

Many of these opportunities are technically open processes, but relationships still play a part.

Three years later, people are focusing on relationships. They understand relationships are the way to go.

They also understand that sometimes the biggest fundraising growth can come from their own funders.

We can show the median first-, second-, and third-year grant for each funder. For example, the first year, they may give $10,000. If they like you and the relationship is good, it may jump to $40,000. In the third year, it may become $56,000.

But you may still be receiving $10,000 because you did not know you could ask for more. You did not know they tend to grow their support.

So we highlight the potential in your existing funder base.

In my opinion, this is by far the best way to go. Of course, there are exceptions. If you are in a capital campaign, you may need to find a large funder who will put their name on it. But day-to-day grantmaking and fundraising in foundation land definitely rely on relationships, and we want to push organizations there as much as possible.

Stephen Halasnik:
Is the relationship between Impala and a nonprofit consultative, or are people mainly using the data Impala has? Are they calling your office and asking how else they can get to what they are trying to do?

Shahar Brukner:
When we built the company and the platform, we said from day one that the product should be tested by how much it does not require us to hold the customer’s hand.

It takes time to understand how we think about the world. It takes time to shift from focusing on open submissions to focusing on relationships.

When people join Impala, we have a robust and human customer success service that helps them understand how to use the platform.

But I am happy to say we also built a good product that does not require people to call us constantly.

It is not just that the data is there and users play with it. We have built it into very specific workflows: research a sector, find the connection, see who your board is connected to, and find the connection between any point A and point B.

The platform is pretty self-explanatory. We have also added a customer success AI agent called Easy, which helps users understand how to navigate the platform. Many customer questions are now solved by speaking with the agent.

To answer your question, it is definitely not primarily a consultative approach.

That said, we are working with a lot of consultants. Many consultants are Impala customers, from some of the biggest firms in the country to much more local shops.

It is on our radar to provide consultants with some kind of marketplace on top of Impala so they can offer their services. For example, if you need someone to write a grant based on something you found, you could contact one consultant. If you need someone to help define your ecosystem, you could contact another.

So far, most users can self-serve.

Stephen Halasnik:
Today’s topic is about how people have gotten more and more data, but it is not helping them. We touched on it earlier, but let’s dive a little deeper. Is your premise that it still comes down to relationships?

Shahar Brukner:
Relationships have weight, but I would take it one step back.

Data does not equal intelligence. It just does not.

Think about a salesperson. I can give that person details about thousands of prospects, including where they work, their email, and their phone number. But if I do not tell them how much budget the prospective buyer has or what industry they work in, it is hard to understand what to do with all that data.

The first thing we said is that data does not equal intelligence.

Then the question becomes: what kind of intelligence do nonprofits and fundraisers need? Intelligence is digested and packaged data connected to a real workflow.

We had our own hunch because we come from nonprofits, but we did not trust only our hunch. We created several advisory committees with some of the top fundraisers in the country and asked them what they needed.

The first thing that came up was the answer to this question: What is your most powerful asset in fundraising?

They all said the same thing: people who care about us. Our donors, our board, and foundations that are already giving to us.

Then the question became: how do you utilize that?

They told us that in a quarterly board meeting, less than 30 minutes may be saved for fundraising. The chief development officer comes in and asks a board member, “Who do you know that you can connect me with?”

But that is not a good question. A board member may know 5,000 people.

So you leave the meeting with the board frustrated because they were not utilized effectively, even though they want to help. The fundraising team also feels bad because they know the board member knows a lot of people, but they do not know who.

We turned that on its head and started building toward that intelligence.

The idea is to turn huge amounts of data into intelligence. The more data you have, the more confusing it can become unless it is packaged into something usable.

Stephen Halasnik:
That makes sense. Last question. Can people get this type of data through ChatGPT or other AI platforms?

Shahar Brukner:
Some of it, yes. Some of this data is becoming available through those platforms, but I would say two things.

First, the context window is much smaller than what we can offer.

If you ask for all the grants the Ford Foundation gave in the last 10 years, on Impala you can get that in one click. With ChatGPT, it may start to struggle. It may ask whether you really want all of the grants or say it needs documents to complete the task.

If you ask for the top 10 grants, you may get that quickly. But in many cases, you want to see the full breadth of what you are researching.

Second, AI tools may give you the data, but they may not connect it into real intelligence or a real action.

If you ask how you are connected to Stephen, for example, a general AI tool may know that there is a Stephen at one organization, but it cannot scan all the people sitting on other boards of other foundations the way we can. We have already done that. We have a database of about 16 million people.

So some of this data is available through other engines, but it is still very far from giving you the intelligence you need.

Stephen Halasnik:
Cool. Thanks for coming on. I’d like to thank Shahar Brukner from Impala for coming on today’s podcast.

If you liked today’s podcast, please feel free to share it with your friends and subscribe on your favorite podcasting app.

Also, if you’re looking for a line of credit for your organization, please feel free to reach out through our website to learn more at nonprofitmbapodcast.com.

Shahar, if anyone wants to get in touch with you, how would they go about doing that?

Shahar Brukner:
They can email me at [email protected], or they can go to our website at www.impala.digital. There is a get-in-touch button there. All of those messages get to me, so you will receive an answer from me.

Stephen Halasnik:
Great. Thanks for coming on today.

Shahar Brukner:
Stephen, thank you so much.

Stephen Halasnik:
I want to remind our listeners that I say this after every podcast because it is heartfelt for me. Every day, you are out there on the front lines trying to help the world become a better place, and we thank you for that.

But keep in mind that you are no good to your employees, your cause, your family, or yourself if you are burned out.

Every day, you need to think about yourself and ask, “What do I need to do today to stay energized?” Maybe it is going for a walk, exercising, grabbing a cup of coffee with a friend, or whatever helps you keep your energy going for the long term.

Solving the world’s problems is not a sprint. It is a marathon, and we need you.

Thank you for listening to the Nonprofit MBA Podcast. Have a fantastic day, everybody.

About our Guest

Shahar Brukner, Founder and CRO of Impala, works on these challenges daily. Impala uses AI to help nonprofits and foundations turn fragmented grantmaking data into actionable insight, making it easier to identify stronger funding opportunities and improve decision-making.