Skip to main content

Cendana Capital, which has been backing seed funds for a decade, has $278 million more to invest

When in 2010, former VC Michael Kim set out to raise a fund that he would invest in a spate of micro VC managers, the investors to which he turned didn’t get it. Why pay Kim and his firm, Cendana Capital,  a management fee on top of the management fees that the VC managers themselves charge?

Fast forward to today, and Kim has apparently proven to his backers that he’s worth the extra cost. Three years after raising $260 million across a handful of vehicles whose capital he plugged into up-and-coming venture firms, Kim is now revealing a fresh $278 million in capital commitments, including $218 million for its fourth flagship fund, and $60 million that Cendana will be managing expressly for the University of Texas endowment.

We talked with Kim last week about how he plans to invest the money, which differs slightly from how he has invested in the past.

Rather than stick solely with U.S.-based seed-stage managers who are raising vehicles of $100 million or less, he will split Cendana into three focus areas. One of these will remain seed-stage managers. A smaller area of focus — but one of growing importance, he said — is pre-seed managers who are managing $50 million or less and mostly funding ideas (and getting roughly 15% of each startup in exchange for the risk).

A third area of growing interest is in international managers. In fact, Kim says Cendana has already backed small venture firms in Australia (Blackbird Ventures), China (Cherubic Ventures, which is a cross-border investor that is also focused on the U.S.), Israel (Entree Capital), and India (Saama Capital), among other spots.

Altogether, Cendana is now managing around $1.2 billion. For its services, it charges its backers a 1% management fee and 10% of its profits atop the 2.5% management fee and 20% “carried interest” that his fund managers collect.

“To be extremely clear about it and transparent,” said Kim, “that’s a stacked fee that’s on top of what our [VC] fund managers charge. So Cendana LPs are paying 3.5% and 30%.” One “might think that seems pretty egregious,” he continued. “But a number of our LPs are either not staffed to go address this market or are too large to actually write smaller checks to these seed funds. And we provide a pretty interesting value proposition to them.”

That’s particularly true, Kim argues, when contrasting Cendana with other, bigger fund managers.

“A lot of these well-known fund of funds are asset gatherers,” he says. “They’re not charging carried interest. They’re in it for the management fee. They have shiny offices around the world, they have hundreds of people working at them, they’re raising billion-dollar-plus kind of funds, and they’re putting 30 to 50 names into each one, so in a way they become index funds. [But[ I don’t think venture is really an asset class. Unlike an ETF that’s focused on the S&P 500, venture capital is where a handful of fund managers capture most of the alpha. Our differentiation is that we’re taking we’re creating very concentrated portfolios.”

Specifically, Cendana typically holds positions in up to 12 funds, plus makes $1 million bets on another handful of more nascent managers that it will fund further if they prove out their theses.

Some of the managers it has backed has outgrown Cendana from an assets standpoint. It caps its investments in funds that are $100 million or less in size.

But over time, it has backed 22 managers over the years. Among them: 11.2 Capital, Accelerator Ventures, Angular Ventures, Bowery Capital, Collaborative Fund, Forerunner Ventures, Founder Collective, Freestyle Capital, IA Ventures, L2 Ventures, Lerer Hippeau, MHS Capital, Montage Ventures, Moxxie Ventures, Neo, NextView Ventures, Silicon Valley Data Capital, Spider Capital, Susa Ventures, Uncork VC (when it was still SoftTech VC), Wave Capital and XYZ Ventures.

As for its pre-seed fund managers, Cendana is now the anchor investors in 10 funds, including Better Tomorrow Ventures, Bolt VC, Engineering Capital, K9 Ventures, Mucker Capital, Notation Capital, PivotNorth Capital, Rhapsody Venture Partners, Root Ventures, and Wonder Ventures.

As for its returns, Kim says that Cendana’s very first fund, a $28.5 million vehicle, is “marked at north of 3x” and “that’s net of everything.”

He’s optimistic that the firm’s numbers will look even better over time. According to Kim, Cendana currently has 38 so-called unicorns in its broader portfolio. It separately hold stakes in 160 companies that are valued at more than $100 million.



from TechCrunch https://ift.tt/31DUsm6
via IFTTT

Comments

Popular posts from this blog

Apple’s AI Push: Everything We Know About Apple Intelligence So Far

Apple’s WWDC 2025 confirmed what many suspected: Apple is finally making a serious leap into artificial intelligence. Dubbed “Apple Intelligence,” the suite of AI-powered tools, enhancements, and integrations marks the company’s biggest software evolution in a decade. But unlike competitors racing to plug AI into everything, Apple is taking a slower, more deliberate approach — one rooted in privacy, on-device processing, and ecosystem synergy. If you’re wondering what Apple Intelligence actually is, how it works, and what it means for your iPhone, iPad, or Mac, you’re in the right place. This article breaks it all down.   What Is Apple Intelligence? Let’s get the terminology clear first. Apple Intelligence isn’t a product — it’s a platform. It’s not just a chatbot. It’s a system-wide integration of generative AI, machine learning, and personal context awareness, embedded across Apple’s OS platforms. Think of it as a foundational AI layer stitched into iOS 18, iPadOS 18, and m...

The Silent Revolution of On-Device AI: Why the Cloud Is No Longer King

Introduction For years, artificial intelligence has meant one thing: the cloud. Whether you’re asking ChatGPT a question, editing a photo with AI tools, or getting recommendations on Netflix — those decisions happen on distant servers, not your device. But that’s changing. Thanks to major advances in silicon, model compression, and memory architecture, AI is quietly migrating from giant data centres to the palm of your hand. Your phone, your laptop, your smartwatch — all are becoming AI engines in their own right. It’s a shift that redefines not just how AI works, but who controls it, how private it is, and what it can do for you. This article explores the rise of on-device AI — how it works, why it matters, and why the cloud’s days as the centre of the AI universe might be numbered. What Is On-Device AI? On-device AI refers to machine learning models that run locally on your smartphone, tablet, laptop, or edge device — without needing constant access to the cloud. In practi...

Max Q: Psyche(d)

In this issue: SpaceX launches NASA asteroid mission, news from Relativity Space and more. © 2023 TechCrunch. All rights reserved. For personal use only. from TechCrunch https://ift.tt/h6Kjrde via IFTTT