Acquire AI is the funding discovery and grant intelligence suite within Aubree, the Philanthropic Intelligence Platform. It autonomously searches funding databases, scores opportunities by mission alignment using an Intelligent Fit Score algorithm, and surfaces the highest-probability grant prospects for your organization — eliminating the manual, high-friction grant hunt that consumes development staff time with low-yield results.

How does Acquire AI's Intelligent Fit Score work?

Acquire AI uses natural language processing (NLP) to analyze your organization's mission statement, program descriptions, geographic focus, and population served, then matches these against the stated priorities of thousands of foundations and government funding sources. Each opportunity receives an Intelligent Fit Score that ranks alignment — so your team only pursues grants where the probability of success is high.

How does Acquire AI fit into the Philanthropic Intelligence Platform?

Acquire AI is the funding growth layer of Aubree's four-suite Philanthropic Intelligence Platform. It works in direct partnership with StewardWise AI — insights about which programs are resonating most with current donors inform the funding searches Acquire AI runs, creating a synergistic growth loop between donor retention and new funding acquisition.

How is Acquire AI different from grant databases nonprofits already use?

Traditional grant databases require a development director to manually search, read, and evaluate each opportunity. Acquire AI inverts this: instead of your staff hunting through hundreds of listings, an autonomous AI engine continuously monitors funding landscapes and proactively delivers ranked, mission-matched opportunities directly to your team — turning a reactive research process into a predictive intelligence function.

What types of funding does Acquire AI discover?

Acquire AI searches across foundation grants, corporate philanthropy programs, government funding sources, and community foundation opportunities. It continuously monitors for new funding announcements and deadline alerts, ensuring your organization never misses a high-fit opportunity due to limited research bandwidth.

What results can nonprofits expect from Acquire AI?

Organizations using Acquire AI typically see a significant reduction in time spent on grant prospecting, an increase in application quality due to better mission alignment, and access to funding opportunities they would not have discovered through manual research. The platform is designed to function as a full-time grant research analyst operating 24/7.

Is Acquire AI available in a bundle?

Yes. Acquire AI is the core of the Revenue Optimizer bundle, paired with StewardWise AI to create a complete retention-plus-acquisition growth engine. It is also included in the full Aubree Philanthropic Intelligence Platform.

Impact Story Match · Agent 02 · StewardWise AI | Aubree

Agent 02 · Story Intelligence · StewardWise AI

We Did Not Just Find That
She Is Leaving. We Found the Story That Brings Her Back.

Impact Story Match maps a donor's giving history, professional background, and mission affinity to the specific program story they are waiting to hear, then generates the appeal email that delivers it. 94/100 match score. Not a random story. The story.

We did not write that email. Aubree wrote it, using Sarah's own data to find the exact story she was waiting to hear. That is not personalization. That is precision stewardship.

94/100 match score. Not a random story. The story.
Donor background cross-referenced: career, foundation priorities, prior giving.
Program story library surfaced from your existing impact data.
Appeal email generated from the match. Precision stewardship, not personalization.

94/100 Match score

3 Data dimensions matched

Automatic Email generated from match

Every donor Has a story waiting for them

Get Started

Every Donor in Your Database Has a Story That Will Resonate With Them Specifically. Nobody Has Had Time to Find It.

When a donor starts showing pre-lapse signals, the instinct is to send the same re-engagement email the organization sends to everyone. First name merge field. A general update on the mission. A soft ask. That email arrives in the inbox of a tech executive who has spent 15 years mentoring women in STEM and whose foundation's stated priority is closing the opportunity gap in technology education. It reads like it was sent to 800 people. Because it was.

The story that would reconnect Sarah Chen to your mission exists in your program database right now. It is the story of a student who was number 47 on your STEM Academy waitlist, whose seat was created by donor investment, who eight months later presented at the Maryland STEM Symposium. That story matches Sarah's professional identity, her philanthropic priorities, and the specific type of impact she is motivated to fund. She just has not heard it yet.

Impact Story Match cross-references every at-risk donor's giving history, professional background, and mission affinity against your program story library and surfaces the specific story with the highest resonance probability. Then it generates the appeal email that delivers it. The result is not a personalized email. It is a precision-matched communication built from that donor's own data, aimed at the exact story they were waiting to hear.

Sarah Chen. 94/100 Match. The Email That Brings Her Back.

Impact Story Match · Sarah Chen · At-Risk Donor

StewardWise AI · Agent 02 · Story Intelligence

Donor Profile · Incoming from Donor Risk Alert

Sarah Chen

VP Engineering, TechCorp · MIT Alumna · Foundation Board Member

3-year donor. Total giving $47,500. Risk score 62 and declining.

15 years mentoring women in STEM at TechCorp and through MIT Alumni Network.

Oakridge Family Foundation board member. Stated priority: closing the technology opportunity gap.

Prior giving to 3 STEM education organizations outside your database.

Mission Affinity Scoring · Cross-Referenced

STEM Education

Youth Workforce Dev

Mentorship Programs

Access and Equity

Higher Ed Pipeline

Program Story Match Found · Analyzing Story Library 94/100 Match Score

Matched Story · STEM Academy Program

Marcus Johnson · STEM Academy · Maryland STEM Symposium

Program: STEM Academy · Cohort Spring 2025 · Outcome: Postsecondary Track

94/100

Marcus Johnson was number 47 on the STEM Academy waitlist. A donor's gift created one additional seat. That seat went to Marcus. Fourteen weeks of instruction, employer mentorship, and a regional competition. Eight months after he was on the waitlist, Marcus presented at the Maryland STEM Symposium, the first student from his school in 11 years. He is applying to University of Maryland computer science.

✓STEM education pathway matches Sarah's 97/100 affinity score and professional background

✓Mentor-created opportunity aligns with Sarah's 15-year mentorship commitment and foundation priority

✓Waitlist-to-symposium arc mirrors the access gap narrative Sarah's foundation funds explicitly

✓University pathway outcome matches Sarah's MIT identity and education equity conviction

Generated Appeal Email · Sarah Chen · Ready to Send

Subject The student your gift made possible.

To Sarah Chen · Personalized from giving history and affinity profile

Opening · Donor as Hero

Sarah, three years ago you made a decision that changed Marcus Johnson's life, even though you have never met him. Your gift created the seat he was waiting for.

Story · Matched to Affinity

Marcus was number 47 on the STEM Academy waitlist. Your investment opened one more seat. Fourteen weeks later he stood on the Maryland STEM Symposium stage, the first student from his school in 11 years. He is applying to computer science at University of Maryland. He had never written a line of code before your gift made his seat possible.

Connection · Professional Identity Mirror

You have spent 15 years opening doors for people who would not have found them otherwise. Marcus's story is what that looks like when it reaches someone who was waiting at number 47. This spring, 23 students are on that same waitlist.

Ask · Calibrated to Giving History

A gift of $15,000 creates six seats in the next STEM Academy cohort. Six students who are currently number 47. Would you make that possible?

This email was not written from a template. It was generated from Sarah's own affinity data, giving history, and professional background, matched against your program story library. That is the difference between personalization and precision stewardship.

Personalization Puts a First Name in a Subject Line. This Finds the Story That Changes the Outcome.

The difference between a re-engagement email that gets deleted and one that restores a major donor relationship is not better timing or a stronger subject line. It is whether the story inside the email is the one that donor was waiting to hear.

Generic Personalization

First name. Same story. Sent to 800 people.

Dear Sarah, we hope this message finds you well. We wanted to share an update on our programs and remind you of the important work your support makes possible. Our STEM Academy served 47 students this quarter. We hope you will consider renewing your support.

Deleted · 21% open rate · 2% conversion

Precision Story Match

Donor's own data. The specific story. Built for her.

Sarah, three years ago you made a decision that changed Marcus Johnson's life. Marcus was number 47 on the waitlist. Your gift created his seat. He stood on the Maryland STEM Symposium stage eight months later. 23 students are on that same waitlist right now.

Opens · Reads · Renews the relationship

The Right Story. For Every Donor. Every Time.

94/100 Match Score

Not a random story from the program library. The story. Impact Story Match cross-references career background, philanthropic priorities, giving history, and mission affinity simultaneously to surface the program story with the highest resonance probability for that specific donor. 94 out of 100 means the data says this is the story.

Three Dimensions Cross-Referenced

Giving history shows what the donor has funded and at what level. Professional background reveals their domain expertise and identity. Foundation priorities expose the specific language of their philanthropic conviction. All three dimensions matched simultaneously against your program story library to find the precise intersection.

Appeal Email Generated from the Match

The match is not a recommendation. It is the input. Impact Story Match generates the appeal email from the matched story automatically, framing the donor as the hero, connecting their professional identity to the program outcome, and calibrating the ask to their giving history. Your development director reviews and sends.

Surfaced from Your Existing Program Data

You do not need to create new stories. You need to surface the stories already in your program database. Every program report, every student outcome, every volunteer testimonial is potential raw material. Impact Story Match reads your existing impact data and builds the story library automatically.

Follows Donor Risk Alert Automatically

When Donor Risk Alert flags Jennifer Martinez or Sarah Chen as at-risk, Impact Story Match fires automatically and surfaces the matched story. The two agents work in sequence. Risk detected. Story matched. Appeal generated. The development director receives the complete retention package: who to contact, what story to tell, and the email ready to send.

Every Program Has Stories Like Marcus. This Finds the Match.

You have the stories. You just have not connected them to the donors they were meant for.

A mentor who stayed in school because of your program. A family that accessed services for the first time. A volunteer who found purpose. Every program generates these stories. Impact Story Match surfaces them from your data and delivers them to the donor who needed to hear that specific one.

From Generic Re-engagement to Precision Stewardship

Without Impact Story Match

Same re-engagement email sent to every at-risk donor regardless of background
First name merge field treated as personalization
Sarah Chen receives a general STEM update that reads like it was sent to 800 people
Marcus Johnson's story sits in a program report Sarah has never seen
Development director manually researches each donor before writing re-engagement copy
Hours spent on research that produces a generic email anyway
Re-engagement rate stays flat because the story never matched the donor

With Impact Story Match

Every at-risk donor matched to the specific story with highest resonance probability
Career, foundation priorities, and giving history cross-referenced simultaneously
Sarah Chen receives the Marcus Johnson story because the data says it is the one
Appeal email generated from the match and ready to send in minutes
Development director reviews and sends. No research. No blank page.
Donor identity activated. The email arrives as a recognition, not an ask.
Precision stewardship at the scale of every at-risk donor in your file

Every Donor in Your Database Has a Story That Will Resonate With Them Specifically.

This finds it and deploys it automatically.

The Story That Brings Sarah Back Is Already in Your Program Data. She Just Has Not Heard It Yet.

Get started and see Impact Story Match surface the right story for every at-risk donor in your file.