Alternative investments — private equity, venture capital, and real estate — have grown into massive asset classes over the last twenty years, from $1 to ~$16 trillion in AUM. The inevitable correlative of this growth is complexity: more strategies, more intricate fund structures, more special-case limited partner (LP) arrangements, more involved audit, and more demanding workflows for finance teams to calculate performance, distributions, fees, sub-closes, capital calls, and many other events.

As in every industry, Excel is the workhorse financial professionals have relied on to handle calculations of arbitrary levels of complexity.  In fund accounting, it is typical for it to be employed twice: once by third-party fund administrators — relied upon by some firms for most finance operations — and again by internal teams to verify their work. But for all its strengths, Excel was not intended to serve as a transactional database, and its very flexibility allows users to create calculation logic too complicated to parse or debug.

Thus, as the industry scales, the cracks in Excel are widening: Spreadsheets multiply, errors compound, and firms risk institutional knowledge walking out the door with each departing employee.  Fund accountants spend days untangling or rebuilding models, reconciliations drag on between admins and teams, and GPs sometimes remain one step removed from the calculations that matter most.

Maybern*’s founders started with a straightforward “Excel to software” premise. A platform that generalized correctly across the breadth of financial “primitive” concepts used by firms would enable them to define their calculation logic lucidly with proper transactional histories, permissions, and audit trails in a single and dynamic performance book-of-record. Moreover, this logic would be simple to execute, and calculations that can take days to prepare could be handled in minutes.

Achieving this simplicity has been no small feat, especially given the diversity of limited-partner agreements (LPAs), side letters, and rounding conventions that must be correctly applied in each calculation. Instantiating this context precisely enough to deliver precision down to the penny requires deep understanding of the domain, an expert delivery methodology, and a calculation engine capable of representing all the nuances in play. The stakes are higher than just efficiency: Clean audits and avoidance of restatements are essential to the LP trust and regulator approval.

From our first conversation with co-founders Ross Mechanic and Ashwin Raghu more than two years ago, it was clear they built Maybern with this reality in mind. Engineers by training, they had lived the problem themselves at Cadre, a real estate investment platform, and immersed themselves so deeply in the mechanics of fund operations that, as one customer put it, “they should have honorary degrees in fund accounting.”

That fluency shows up in the product, a canonical data model for fund accounting that is built to serve as the system of record for every calculation. Each time a fund is onboarded, Maybern ingests its LPAs, side letters, and historical calculations, then abstracts them into reusable primitives: fee rules, waterfall tiers, rounding conventions, and more. These primitives form the foundation of a library that grows to capture the quirks and edge cases of the industry.

Over time, we think this library becomes something larger: a living alphabet of fund economics, powering a scalable system that makes even the most complex fund structures simple to model, audit, and trust.

In just 18 months since launch, Maybern is already partnering with some of the largest funds across the alternatives landscape. CFOs describe how Maybern provides them leverage as operational complexity grows — ensuring accuracy, reducing latency in critical calculations, and delivering both tighter control and greater transparency. For internal fund accounting teams, Maybern is unlocking time savings and beginning to enable more-sophisticated forms of reporting and scenario modeling. The platform is also laying the foundation for AI-driven LPA ingestion and auditability, providing not just results but clear explanations of every calculation.

Battery is proud to partner with the Maybern team on this journey and to announce that we are leading the company’s $50 million Series B, alongside our peers at Primary, Human Capital, and MetaProp Ventures.