Maybern

Private markets run on precision, but too often rely on tools that cannot explain themselves. Trillions under management, strategies getting sharper, expectations rising, yet the core machinery still hums like it is 2008. Excel tabs stacked like Jenga, institutional memory hiding in cells, and fund CFOs spending more time proving numbers than using them. In New York City, Maybern stepped into that gap in 2021 with a simple but loaded premise from Ross Mechanic and Ashwin Raghu: if the data is fractured, the decisions will be too. In a startup ecosystem obsessed with front-end velocity, they chose to rebuild the engine room.

Ross Mechanic built fund accounting systems at Cadre and saw the strain up close, where billion dollar funds leaned on spreadsheets that could not explain themselves. Ashwin Raghu scaled data systems at Cadre and before that in high intensity environments where structure is survival. Together they are not guessing at the problem, they lived it. That shows up in the product. Maybern is not chasing surface level automation. It is building a single performance book of record that connects the general ledger, investor data, and fund terms into something that actually speaks.

The pitch lands because the numbers do. $76M raised, including a $50M Series B led by Battery Ventures. More than $80B in assets managed on platform. Growth moving at 4.6x year over year. Recognition on the 2026 Forbes Fintech 50. Customers like Madison Realty Capital and Gauge Capital are not testing toys, they are running real funds on it. When those firms move, the room pays attention, and the startup ecosystem takes notes.

What makes Maybern hit different is how it treats complexity. Capital calls, waterfalls, distributions, the stuff that usually lives in fragile models, now runs through governed workflows with audit trails that can stand up in daylight. The system is built to answer questions in seconds that used to take days. And beneath it all is a data model designed for advanced automation, not retrofitted shortcuts. Clean inputs, structured logic, real outputs. That is where this goes from software to leverage, and where the startup ecosystem starts to feel second-order effects.

The bench matters too. Tiffany Simonsen brings deep fund operations experience into client reality, making sure the product does not drift from how funds actually run. Riley Thomas drives go to market with the kind of pattern recognition that turns early traction into repeatable motion. This is not theory meeting code. It is operators and engineers building in the same room, solving for edge cases before they become problems.

Zoom out and the timing sharpens. Private markets sit around the $15T–$16T mark and keep expanding. More capital, more scrutiny, more pressure to move faster without adding headcount. The old tools bend under that weight. Maybern is building for that pressure, not avoiding it. In a startup ecosystem that rewards speed, they are betting on precision, and that combination tends to compound.

They are hiring across engineering, product, and go to market roles in New York. If you care about data that holds up under pressure and systems that earn trust instead of asking for it, this is one to watch closely. Get in the room while the category is still taking shape.