Founded MMXXVI·New York·AI-native

We run the business of learning.

AI-native solutions, not more headcount.

Axia installs AI capability inside universities. Specific systems that replace measurable functions. Institutionally owned from day one.

Bust · Marcus Aurelius, c. 170 AD
Marble · carved
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Scroll · Methodology
Methodology

Three stages. Each one earns its place.

We diagnose first because we are operators, not advisors. Then we design a specific system against a specific function. Then we deliver it, inside the institution's stack.

STAGE · 01
Diagnose

Proprietary Health Score across finance, enrollment, outcomes, regulatory standing, operations, AI readiness, and international reach.

FindingsRoadmapBaselines
1–3 months
STAGE · 02
Design

A specific system for a specific measurable function. No abstractions. No platform sales. We scope to what replaces an existing line-item.

Function specAgent mapKPIs
4–6 weeks
STAGE · 03
Deliver

We build it inside the institution's stack. Production from week one — not a pilot that never ships.

AI SolutionsAutonomous Agents
8–16 weeks
After delivery

The institution owns the system. The workspace, the agents, the runbooks, the data. We retain for optimization, not dependence. No revenue share on tuition. No ten-year lock-in. No seat at the table we did not earn.

The process · Engagement timeline

From first call to running institution.

Twelve weeks to a working diagnostic and a signed implementation plan. Nine months to production systems running inside the institution. Then we stay — for optimization, not dependence.

I
Week 1–2

Discovery

Operational audit. Pain point mapping. Financial baseline. We pull your public data before the first meeting.

II
Week 3–8

Diagnostic

Opportunity modeling. Technology assessment. Quick wins executing while the full diagnostic runs.

III
Week 9–12

Design

Platform architecture. Revenue projections. Implementation plan. Board-ready deliverables.

IV
Month 4–9

Implementation

AI agents live. Digital programs launched. Marketing war room running. Revenue metrics tracked weekly.

V
Ongoing

Operations

Monthly dashboards. Quarterly optimization. Revenue share means our success is tied to yours.

12 weeks from first call to implementation plan. 9 months to production. After that, we stay for optimization — not dependence.
Scale: one bar unit ≈ two weeks of engagement.
· Origin

Axia is new. The operators are not.

Before Axia existed, Juan Cruz Rabbat spent two decades inside a family education group in Latin America. Enrollment systems, academic ops, digital program delivery, retention. Built and run in markets that never had a 2U, never had a McKinsey.

150,000
Students
served
600+
Academic
programs
5
Institutions
operated
20 yr
End-to-end
experience
Austral Latin America
North America Boreal
I.

Then we looked north. Thousands of small US institutions are closing. 2U filed Chapter 11. Sixty-plus regional universities have shut since 2020. The sector is under-served by the consultancies it can afford and over-charged by the OPMs it cannot afford to keep.

II.

The gap is operational, not strategic. These institutions know what the problem is. They do not have the engine to fix it.

III.

Axia is that engine. Rebuilt AI-native. Installed inside the institution. Owned by them from day one.

Positioning

We define ourselves by what we refuse.

Every sentence earns its place. So does every engagement model. Here is what Axia is — and what it will never be.

What we are not
  • Another LLM wrapper sold on vibes.
  • An OPM taking 60% of tuition for ten years.
  • McKinsey-style deliverable theater.
  • A marketing agency with a chatbot bolted on.
  • AI "transformation" in the abstract.
What we are
  • AI capability installed inside the client.
  • Systems that replace measurable functions.
  • Operators first. Diagnose before we prescribe.
  • One stack, many buyers. Compounding, not bespoke.
  • Institutional ownership from day one.
Three product lines · One AI stack

Diagnostic, war room, academy.

Each line installs on the same infrastructure. Each replaces a specific function an institution already pays for. $240K baseline, rev share on short programs. Blended ACV target $400K.

If your institution has under 5,000 FTE and under $100M revenue, and you are feeling the enrollment cliff — this is built for you.
LINE · I

Operational Diagnostic

Proprietary Health Score across seven dimensions — financial health, enrollment, outcomes, regulatory, ops, AI readiness, international. The entry point of every relationship.

Duration
1–3 months
Entry price
$45K
LINE · II

Marketing War Room

Enrollment-marketing AI plus managed delivery. Replaces or augments internal marketing teams. Funnel optimization, CRM ops, paid media, international lead management.

Engagement
$20K / mo
Channels
Full stack
LINE · III

Digital Academy

Academy infrastructure, short-program builder, instructional-design agents, tutoring agents. Recurring revenue plus rev share on short-program tuition.

Model
Recurring + RS
Surface
Canvas
Begin with a diagnostic

One buyer at a time.
The institution we diagnose next could be yours.

Three-to-six-week diagnostic. Seven-dimension Health Score. Implementation roadmap. If we are the right partner, the diagnostic earns it. If we are not, you keep the findings.