350 transactions. Five decades. One playbook.
We invest in operating companies and platforms that can compound for a long time. Then we work alongside their teams to make sure they do.
Two themes. One thesis.
Today we deploy across two interlocking priorities: building inside artificial intelligence, and acquiring the companies whose value AI is about to transform.
Artificial intelligence
Through our M42 unit, Richmont develops psychometric AI — models that find pattern in behavioral, cognitive, and operational data. We deploy it inside our portfolio and partner with companies building the layers above and below.
Operating companies
We acquire and partner with businesses that operate inside or alongside AI — and traditional operators where AI can change the unit economics. Where we sit, the answer is usually a combination of capital, talent, and software.
A portfolio across cycles, geographies, and categories.
A representative slice of the more than 350 transactions Richmont has led, co-led, or backed since 1976.
Our diligence engine reads the data that résumés don't show.
Most M&A failure is cultural. Most diligence reports don't go near the cultural data — they can't. M42 ingests behavioral, leadership, and stakeholder signal at scale and produces a reading on cultural fit, leadership resistance, and post-close integration risk before we sign a term sheet.
The same models drive operational improvement after close: identifying cohorts most likely to churn, leadership pairs most likely to succeed, and integration sequences most likely to land.
M42 inputs
- Public communications and disclosures
- Employee sentiment and review data
- Leadership cadence and decision history
- Customer and stakeholder signal
- Operational and financial telemetry