AI transformation in weeks, not years.
The models work. Your data doesn’t.
80%
of AI projects never reach production
Because the data underneath isn’t ready.
Your AI asked “who is the customer?” This is what it got back.
CRM
Customer
Sales pipeline
EHR
Patient
Clinical record
Benefits
Member
Enrollment file
Billing
Account
Invoice entity
Support
Client
Ticket owner
of one entity, across a ten-portco portfolio
Same entity. Five labels. Zero ground truth for AI.
That’s the Babel Tax.
Every acquisition multiplies your AI problem. Unless it doesn’t.
Portco fifty doesn’t re-map portcos one through forty-nine.
What it actually does.
What your portcos send
Portco A · CRM
- cust_id
- A4729
- name
- "Jonas, S."
- sjonas@acme.com
Portco B · EHR
- PatientID
- 82-S-LON
- first
- Sara
- last
- Jonas
- —
Portco C · Billing
- acct_num
- 10947
- billing_name
- "Sara Jonas-Lee"
- email_addr
- sjlee@acme.com
What your AI sees
Resolved entity
- entity_id
- mtn-7f93a…
- name
- Sara Jonas-Lee
- emails
- 2
- sources
- Portco A, B, C
- status
- active
Illustrative example. Real customer data is never used in marketing materials.
Three things get faster. Permanently.
Weeks, not years.
From new portco to AI-ready data.
A handful, not a department.
3–5 engineers instead of 15–25. Same AI output.
Maintenance stays flat.
<1 hr/week at 50+ portcos. Conventional: 2–3 engineers per portco.
The 6% who get AI to work — one company in seventeen — share one thing.
They paid down the Babel Tax. They wrote down what “customer” means — everywhere, the same way — so their AI could read it. The unglamorous architectural work.
One more thing
Investors expect AI ROI in six months…
…CEOs need two to four years. Longer than half your active holds.
Only one variable closes that gap. The data layer.
Bring us your messiest portfolio.
Your systems. Your portcos. We’ll show you what the data layer sees in two weeks.
A 30-minute review of where your portcos are stuck on AI — and what it would take to ship.