Results
Two operational restructures. The AI worked before the commercial model did.
iAdvize
$0 to $10M+ AI ARR in 24 months. Collapsed 18 products into two: one vertical AI agent, one SaaS add-on, deployed inside a B2B vertical SaaS platform. Sales cycles compressed from 9 months to 60 days. Trial-to-paid conversion tripled. AI ARR overtook legacy SaaS revenue within the hold period.
$0→$10M
AI ARR
18→2
Product reset
9mo→60d
Sales cycle
3x
Trial-to-paid
Consumption
Pricing model
AI-first
GTM rebuilt
Directly
Promoted to CEO when obligations exceeded cash. Rebuilt cost architecture and deployed AI automation contributing an estimated 50% of EBITDA at exit. 22% EBITDA margin, sustained for two years. Led the complete exit process as CEO, from advisor selection through diligence, negotiation, and board coordination. Asset sale to a PE-backed acquirer.
$3.7M→$8.1M
ARR
22%
EBITDA margin
~50%
EBITDA at exit
PE exit
Asset sale
Outcome
Per-resolution pricing
PE-backed
Acquirer
Principles
- 01
The AI transition is a re-founding, not an upgrade.
- 02
The bottleneck is commercial infrastructure that converts AI into revenue quality.
- 03
Outcome pricing is the destination. Usage pricing is the bridge.
- 04
The renewal is the new sale. AI only renews when it moves a line on the customer’s P&L.
- 05
Durable EBITDA comes from aligning price to value.
The frameworks behind these results
If your portfolio company has AI that isn't driving EBITDA, I've solved that problem twice.