Key Takeaways
- Inflexion managing partner Flor Kassai tracks AI return on investment through a single operational metric: first-party direct origination meetings with executive leadership.
- Direct meetings across Inflexion's six target sectors expanded by 25% quarter-over-quarter after integrating AI screening into the pipeline workflow.
- The buyout firm uses AI algorithms to filter vertical markets against specific fund criteria, replacing manual desk research and secondary data gathering.
- Time saved from desk analysis gets redirected into relationship building, supporting Inflexion's strategy of nurturing founder ties for up to a decade before transacting.
- Kassai reviews the meeting origination figures with the full investment team once a month to hold dealmakers accountable for turning screening speed into off-market access.
Sourcing Speed Only Matters if It Buys Face Time
Private equity sponsors often treat artificial intelligence as an administrative cost-saver. They deploy tools to summarize confidential information memorandums, write investment committee memos, or automate standard compliance filings. Flor Kassai, managing partner and head of buyout at Inflexion, runs the workflow in the opposite direction. For Inflexion, algorithmic screening exists for one reason: to pull investment professionals away from screens and put them in front of founders.
Inflexion applies AI algorithms to map its six core target sectors and their underlying sub-sectors. The software filters target companies against strict fund criteria, flagging off-market assets without requiring an associate to spend weeks reading industry reports or assembling market maps manually.
As Kassai explained to Hugh MacArthur on Dry Powder, the technology delivers speed where it matters most: “AI is giving us a massive edge now, because it's helping us identify opportunities, companies that meet our criteria a lot faster.” (play from 14:47)
The real arbitrage is how the firm uses the hours it recovers. Instead of asking associates to produce more desk work or expand static deal tracking logs, Inflexion converts that operational margin directly into human contact. “It means spending less time on our desks doing the research, because we use these AI tools to help us do that,” (play from 15:08) Kassai said. “And we spend that time instead in person, face-to-face, building relationships.” (play from 15:18)
In mid-market buyouts, proprietary sourcing requires patience. Inflexion often courts founders for up to ten years before signing a deal. Automating the early screening step allows the firm to identify targets sooner, opening a direct dialogue years before an investment bank launches a competitive auction.
The Monthly Metric Kassai Shows Her Team
Many private equity leadership teams struggle to establish clear returns on their software and technology investments. They track tool logins, data query volumes, or self-reported employee satisfaction scores. None of those metrics reveal whether the balance sheet is benefiting.
Kassai stripped the equation down to a single production KPI: direct origination meetings booked with executive teams. Every thirty days, she gathers the investment team to review the data.
The early results show measurable acceleration. Kassai noted that direct founder meetings have increased by 25% quarter-over-quarter across the firm. That growth rate reflects an expanding pipeline of primary relationships rather than just a higher volume of cold outreach emails.
By measuring the front end of the pipeline this way, Kassai eliminates the productivity theater that often accompanies technology rollouts. Dealmakers cannot claim they are using automated tools effectively if their calendar does not show a direct rise in first-party founder discussions.
Why It Matters
Intermediaries and broad auctions continue to compress deal returns across the mid-market. By indexing technology spend directly to proprietary executive access, Inflexion demonstrates how sponsors can industrialize off-market sourcing without turning the firm into a robotic mass-mailer. As AI reduces the cost of raw data analysis to zero, competitive advantage shifts entirely to direct founder relationships that algorithms cannot replace.