Exploring Alumni Ventures’ AI Fund

Can you give us a brief overview of Alumni Ventures’ AI Fund?

The AI Fund focuses on innovative AI and machine learning investments. We will target ~20-30 AI-related deals diversified in terms of sector, stage, region, and investor syndicate to ensure a broad coverage of opportunities — a cornerstone of Alumni Ventures’ investing strategy. We’ll also have the capability to provide support to strongly performing companies in their later rounds, as the fund will maintain ~20-25% reserves for follow-on investments.

What kind of opportunities are present within the AI space?

Across many fields, industries, and sectors, AI and machine learning technologies are having disruptive and transformative effects. Fintechs are increasingly coming to rely on the scalability of machine learning to sift through and interpret incredibly large data sets to help detect customer and market signals, plus inform financial forecasts. Tech giants including Nvidia and Tesla are developing dedicated AI hardware to guide autonomous vehicles. Even legacy financial institutions are swiftly adopting AI to help with automated fraud and consumer protection. 

Because of AI’s pronounced impact and the fast-moving nature of technical advancement, investments at the right time and behind the right team have the chance to generate outsized returns and fundamental changes across vastly different industries. Much in the same way tech visionaries in the ’70s, ’80s, and ‘90s grasped the paradigm shifts of mini computers moving to personal computers to the internet and then to mobile phones, experts and engineers are now turning to AI to create entirely new markets and solve extraordinarily difficult challenges. We are committed to finding and investing in entrepreneurs and companies willing to challenge the status quo and innovate within the AI/ML space.

What qualities do AI companies possess that make them attractive for investment?

When it comes to investments in AI companies, we closely scrutinize for deep technical credentials, commercial sensibility, and ideally, prior entrepreneurial success of the leadership team. Especially pronounced in software and hardware development is the need for intellectual property, patents, know-how, and trade secrets to establish competitive moats. Finally, we apply our conventional diligence metrics around the company’s business model, its monetization path, scalability and upside potential, how mission-critical is the solution, capital frugality, can the team scale with the business, the lead investor’s conviction and commitment to the company, etc., to determine the business’ potential.

How will Alumni Ventures oversee this fund?

Our deal sourcing, vetting, and investing efforts are led by our Focused Funds team, including Managing Partner Lacey Farrell Johnson (Boston) and Principal Jonathan Mo (New York). Lacey has held several key investing roles during her time at Alumni Ventures and previously worked at JP. Morgan, Goldman Sachs, and CareGroup Investment Office. Before joining our firm, Jonathan performed deep technical diligence in AI and machine learning and other verticals at 11.2 Capital, Avery Dennison Ventures, and Silicon Valley Bank.

In addition to direct sourcing by the Focused Fund team, we will leverage the deal flow sourced by our more than 50 in-house investing professionals, geographically dispersed across six U.S. offices, all in key venture hubs. Every member of our team brings unique experience and a broad network of entrepreneurs, industry experts, and fellow VCs to our deal sourcing pipeline.

From among all the deals that Alumni Ventures will invest in during the upcoming year, we will select ~20-30 AI investments for this fund. Each selection will also meet our internal guidelines for diversification across stage, region, lead investor, and geography. In other words, an investor in the AI Fund will own a diversified portfolio of companies, though exclusively developing unique AI and machine learning applications.

How do you source promising opportunities for the fund?

Deals are sourced from the extensive use of our network from across the investing world, including the more than 150 venture capitalists we co-invest with, our more than 6,000 AV investors, and our community of 600,000 subscribers and supporters. It’s this exclusive, multi-threaded community that assists with sourcing deal flow and capital, as well as connections and customers for our portfolio investments.

Once a deal is sourced, Alumni Ventures then employs its rigorous due diligence process, which includes the preparation of confidential due diligence report, the completion of proprietary scorecards by multiple parties, and the approval of a formal investment committee before the company is selected for investment. In this manner, we are able to ensure we build a portfolio of high-potential deals while upholding the core investment thesis of the fund. 

Can you provide examples of Alumni Ventures’ past investments in AI or machine learning?

One of our showcase AI investments is Dataminr, a real-time information discovery platform that uses AI and machine learning to detect and relay critical events to businesses, governments, and prominent news organizations. The platform detects early signs of high-impact events, such as extreme weather events or disease outbreaks, from publicly available data and social media platforms. AV contributed to Dataminr’s $392 million Series E, and the company recently announced a $475 million round raised at a $4.1 billion valuation.¹

As another example, in April 2021, AV invested in Groq, an AI semiconductor designer and manufacturer founded by former Google AI engineer Jonathan Ross. In contrast to its competitors, Groq takes a compiler-led design approach, enabling their customers to easily and quickly deploy high-performance-per-watt systems. The ability to process immense amounts of data in a cost-effective and scalable manner are especially attractive to Groq’s prospective customers, including autonomous vehicle startups and some of the largest cloud service providers in tech.

These deals exemplify the kinds of AI opportunities we’re drawn to, where proven talent intersects with enormous market potential by directly building or supporting AI models and systems. 

If you’re interested in seeing more case studies, we invite you to review our fund materials or connect with us.

¹To see the performance of each exited investment for all Alumni Ventures funds over the last twelve months and our historical performance since 2014, click here.