The Foundation Deep Reasoning Our Story Our Team Careers Press The Signal Solution See It Live
NEWS The Signal Solution — new enrollment playbook by Geoff Baird & Teege Mettille → | View all announcements →

Undergraduate · Graduate · Adult & Non-Traditional

Enrollment's First Thinking Engine.

The strategic thinking of your most experienced enrollment leader — applied to every student in your funnel, every day.

Even the best enrollment teams can only deeply assess just 3–4% of their funnel.
enroll ml gives every counselor a complete AI-driven read on every student — before their day even starts.

See how it works
↓
The Distinction

Most AI automates what humans do.
The Thinking Engine amplifies what your best humans are capable of.

enroll ml isn't here to replace your counselors. It's here to make every one of them disproportionately more effective — with more information, more precision, and more time for the relationships that actually move students to yes.

Why an Enrollment Thinking Engine

Same score. Completely different students.
But what does it mean? And what should you do?

Assessing the true state of any applicant would be easy with just four signals. The enrollment thinking engine pattern matches across hundreds — going beyond what students do, to understand what it means.

Predicted Score: 74  ·  Both students These two students share the same predicted score. A conventional model sees four identical milestones. The enrollment thinking engine sees something entirely different.
T
Tony
5 weeks
Campus Visit
2 weeks
Started App incomplete
scattered
28 Min Web short bursts
2 weeks
Email Open skimmed, no clicks
A
Amanda
4 days
Started App
next day
28 Min Web one session
2 days
Campus Visit
same day
Email Open lingered on aid
· · · still waiting · · ·

What a predictive model sees

Four milestones completed. Score: 74. Same nurture sequence. No distinction between five weeks of drift and four days of momentum.

What the enrollment thinking engine sees

Tony is drifting. Amanda is deciding — and her aid hesitation is the real barrier. Two students. Two strategies. Right now.

Thinking Engine What’s happening beneath the surface
138 activity records · 18 score state changes analyzed
Score trajectory Peak 85 → current 55. 18 state changes tracked. Inflection point identified.
Communication gap 73 days of silence detected. Signal separated from noise across 138 activity records.
Behavioral contradiction Early commitment signals contradict current silence. Diagnosis: not disengaged. Stuck.
Relational capital Insufficient for a logistical push. Trust-building required before next ask.
Benchmarked against 10,000+ students at the same score band and funnel stage.
Output One psychological thesis. Four communications generated. Counselor voice and guardrails applied.

This is four signals and two students. Enrollment’s First Thinking Engine reasons across hundreds of behavioral signals — for every student in your funnel, simultaneously, before your team’s day even starts.

The Foundation

Where enroll ml sits.

enroll ml isn't an AI feature inside an enrollment product. It's the foundational reasoning layer that reads signals across all of them—surfacing a deeper understanding of each applicant, what matters and why, and exactly what to do next.

Your Tools
⊞CRM
◯Chat & Community
◈Marketing
◎Search
◇Fin Aid
△Portal
Deep Reasoning
Foundation

enroll ml

AI Deep Reasoning Layer
Ingests & Pattern Match 800 native +
engineered signals
Processing student, funnel,
counselor, class
Reasoning Mode Machine learning
pattern recognition
AI behavioral analysis
Output
Prioritization Where to focus time
Coaching What to say
Strategy Where to focus
Understanding Student Motivation
Message Creation email, phone script
& notes, text

The Power of AI Reasoning to Transform Enrollment

The challenge of enrollment: hundreds of data inputs to process, complex behavioral patterns, noise and silence, critical time windows, signals both visible and invisible. enroll ml keeps track and makes sense of it all.

enroll ml doesn't just calculate probability—it reasons through each student's journey the way your best counselors would, surfacing the why, the why now, and the exact next step to build trust and drive commitment.

Taylor Martinez • Business Administration Applied
Behavioral Signals in Pattern
0
Far beyond profiles or simple actions—enroll ml decodes how hundreds of micro-behaviors work together to tell each student's real story.
Location on Behavioral Curve
Analyzing signals...
One action is a data point. We match each student's behavioral pattern to the journey of those who said yes—revealing where they are and how they've moved. Probabilities let you watch. Pattern matching lets you intervene.
Commitment Proximity
—
Intervention Window
—
◆ The Unspoken Truth
This is what seasoned enrollment pros do instinctively—read the signals, spot the hesitation, name the real barrier. Deep reasoning makes that intuition scalable.

Not just what they did—when they did it, how it changed, and what they didn't do. The pattern across all three reveals intent no single metric ever could.
Temporal Response pacing: slowing Contact gap: 12 days Return interval: widening
Behavioral Email opens ↔ web visits: mismatched Aid calculator: 3x Tuition page: 4x
Absence Award letter: unopened Counselor outreach: none Housing intent: no signal
The Right Approach Before the message comes the posture. Deep reasoning coaches your team on the emotional stance this student needs—empathy vs. urgency, space vs. push.
◆ Coaching Guidance

The Right Response Beyond mail merge. Guidance crafted for this student's barrier, this counselor's voice, this institution's mission—outreach with purpose, not just personalization.
✉ Personalized Outreach
Subject: A quick note about your financial aid
Full toolkit: SMS Call Script Voicemail

Deep Reasoning

From pattern to person.

The behavioral signals are just the beginning. What happens next is what no predictive model has ever done: we reason.

enroll ml doesn't hand you a score and walk away. It thinks through each student the way your sharpest enrollment leader would—if they had unlimited time and perfect memory.

The Forensic Read

What does this student's behavior actually mean? Not what they clicked—what they're signaling. Are they accelerating or drifting? Engaged or performing engagement?

The Psychological Diagnosis

Why are they hesitating? Is it decision paralysis, cost anxiety, or something unspoken? The AI names the barrier—not guesses at it.

The Guidance

What to do, what to say, how to say it. Not generic advice. Specific direction tuned to this student, this moment, this counselor.

The Say/Do Gap

Students say one thing in emails. Their behavior says something else. Deep reasoning exposes the gap—and tells you which signal to trust.

"While her email tone is enthusiastic, the forensic reality of her empty checklist suggests she is masking deep confusion about the next steps."

The Old Question

Will this student enroll?

The New Question

What does this student need to say yes?

What Changes

Right now, 96% of your funnel doesn't get strategic thinking. What if it did?

Your team knows how to send emails and run reports. Every platform in your stack can do that. What they can't do is replicate the deep strategic thinking that actually moves a student from maybe to yes. Reading hundreds of behavioral signals simultaneously, seeing patterns no human can see across timing, sequence, and silence, and producing the kind of thoughtful, student-specific assessment that today only happens when your most experienced leader has time to sit with a file. For 96% of your funnel, that thinking never happens. They get activity-based workflow instead of deeply reasoned analysis. enroll ml closes that gap.

Hundreds of students
invisible to conventional analytics — found, reached, and enrolled because behavioral signals revealed intent that no dashboard or lead score would have surfaced
"I don't know how anyone ever did this job without it."
— First-year admissions counselor, upon seeing enroll ml for the first time
"
enroll ml has become a foundational element in how we're modernizing student recruitment. It's changing not just what we do, but where we invest our time and resources. This work positions us to recruit smarter, not just harder, in a rapidly changing landscape.
Senior Enrollment Leader Private University, Midwest
"
We knew what it would do for the admissions team; what we found is that the groundwork we're laying through faculty engagement with prospective students has also positively impacted our recruitment efforts. I view enroll ml as a foundational element in how our team thinks and engages with students.
Director of Admissions Public University, West
"
It has shifted how the team views the admission funnel — from a linear process to a dynamic system of signals. Counselors now know who to contact, why they're reaching out, and how to tailor the conversation. The guesswork is gone.
Vice President of Enrollment Private University

The Mind Behind It

This isn't ChatGPT with a CRM plugin.

Generic AI invents when it doesn't know. We built something different: a cognitive architecture trained on enrollment-specific behavioral science, constrained by what it can actually prove, designed to reveal truth—not generate plausible fiction.

Behavioral Science Core

Every insight filtered through proven decision-making frameworks. Theory first, always.

Time as Truth

The same behavior means different things at different moments. We see patterns through time.

Relational Intelligence

Knows when you've earned the right to ask. Protects students from premature pressure.

Honest Uncertainty

Separates what it knows from what it suspects. No hallucinated confidence.

Transparent Reasoning

Shows its work. Every recommendation comes with the logic behind it.

The Foundational Layer

Every tool you've invested in just got smarter.

Your CRM. Your marketing platform. Your chatbot. Your search tools. Your financial aid system. Each one captures signals. None of them talk to each other. None of them reason.

enroll ml is the foundational AI that pulls every signal together—even from applications with their own AI—and creates the complete picture of each student. Point solutions come and go. The reasoning layer compounds.

CRM activity chatbot logs search behavior email opens portal logins FAFSA status event reg text replies app progress web sessions aid calculator video views form starts doc uploads parent portal housing clicks major pages tour signups deadline alerts counselor calls scholarship views compare pages tuition calc chat transcripts campaign clicks social refs repeat visits session depth time on site return gaps
CRM Marketing Chatbot Search Portal Financial Aid

enroll ml

Deep Reasoning

The Origin

We didn't set out to build a company. We set out to solve an impossible problem.

I came to higher education from the outside. Thirty-five years in enterprise computing, mobile technology, major consumer brands. When I stepped into enrollment, I expected to find sophisticated systems, clear analytics, strategic clarity.

Instead, I found brilliant people drowning in data they couldn't interpret. Counselors making gut calls on hundreds of students because that's all they had. Leaders reporting metrics that everyone knew didn't matter, because the metrics that did matter were invisible.

The problem wasn't a lack of data. It was a lack of vision.

We couldn't see what was actually happening in a student's decision. We could see clicks and opens and visits. We could calculate probability. But we couldn't see intent. We couldn't see fear. We couldn't see the moment when a student went from "maybe" to "gone."

So we built something to see it.

We didn't build it to sell. We built it to use. For two years, we ran it ourselves. We proved it. We refined it. We discovered things about student behavior that no one had ever seen before, because no one had ever had the tools to look.

What we found changed everything we thought we knew about enrollment.

Now we're sharing it. Not because we want to sell software. Because we believe every institution deserves to see what we've seen.

Geoff Baird
Founder & CEO

In a World of AI Features

enroll ml is foundation, not feature.

In the high-stakes world of enrollment, advanced AI features are transforming admissions—and that's a good thing. But features alone don't make an AI-driven team. That requires a foundational layer: the processing intelligence that connects every signal, communication, sentiment, and behavior—and works side by side with your team to fully integrate artificial intelligence with human intelligence.

enroll ml is that layer. It's like having your own team of ML and AI engineers (who also happen to be deep, well-practiced enrollment management experts) dedicated to enrollment intelligence—without the impossible hire.

Partners find more students in the movable middle. They catch melt before it happens. Counselors work as strategists. Leaders get time back to lead.

Deep Reasoning in Use Across the Country

Map showing enroll ml partner states across the US

enroll ml is in use by hundreds of admissions counselors and their leadership teams across 20+ states.

We don't publish our partner list—many consider enroll ml a competitive advantage. But we'll be happy to connect you with a partner who can describe firsthand the transformative power of enroll ml.

Read or listen: Hear more from Geoff Baird on enroll ml and the future of AI-driven admissions
Spark & Scale Spark & Scale with Mickey Baines VineDown VineDown with Emily Smith The Application The Application with Allison Turcio Enrollify Enrollify with Scott Cline

Go Deeper

The Signal Solution

The book that started the movement. Co-authored by Geoff Baird and Teege Mettille, it's the thinking behind the platform—and the playbook for AI-driven enrollment transformation.

Read About the Book →

Foundation, Not Feature

The students you're meant to serve are waiting to be seen.

Hundreds of enrollment leaders and their counselors have already tapped into the power of AI deep reasoning. They're seeing patterns they never knew existed. They're reaching students they would have lost. They're operating with clarity they've never had.

The question isn't whether this is the future. The question is when you'll be part of it.

I am interested in learning more about:
2024 GSV Cup 50
Google Cloud Partner
HolonIQ North America Edtech 200