"We spent a decade building revenue engines. What we realized: the tool stack is completely broken. We give reps $4,000 worth of software to find an email address and dial a phone number automatically... and then give them absolutely zero help on what to actually say when the buyer picks up."
Every day, thousands of B2B transactions are won or lost not on product superiority, but on behavioral mismatch. We built RevSage.ai to fix this.
Our first act was building MeetMinutes. We processed millions of hours of sales conversations, looking for patterns. What we found was that while most companies were rushing to use LLMs to summarize calls or write faster spam, they were missing the actual signal: the outcomes.
We realized that the real moat isn't a better summarization prompt. It's the dataset of which specific interventions (a technical whitepaper, a warm intro, a change in tone) actually caused a closed-won deal, controlled for the buyer's cohort.
So we built an architecture that does what frontier LLMs can't do out of the box: causal inference on human behavior. We are giving every revenue team the ability to act not just on what was said, but on what needs to be done.
+ 5 awesome team members in Engineering, Data Science, and Design.
We are actively hiring applied ML engineers, causal inference researchers, and GTM builders.