Exploring Alumni Ventures’ AI Fund

AV’s AI Fund features promising companies leveraging artificial intelligence, machine learning, and big data technologies.

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6 min

Over the past decade, artificial intelligence and machine learning have rapidly become some of the most important — and lucrative — modern advancements in technology. From autonomous driving to natural language processing and predictive modeling, AI has become a crucial component of emerging technologies that are reshaping many industries and sectors. Demand for innovative AI tech is continuing to grow rapidly, with the global market value projected to reach nearly $300 billion by 2026. Alumni Ventures’ AI Fund is dedicated to AI and machine learning opportunities that have the potential to provide lucrative returns and redefine the boundaries of what’s possible with AI. We discussed our AI Fund, its thesis, and its outlook with Chief Investment Officer Anton Simunovic.

AI Fund Open Through Q1 2023

Our AI Fund will invest in a diversified portfolio of ~20-30 companies applying AI, machine learning, big data, and related technologies. The fund will be invested over ~12-18 months with a large reserve (~20-25%) for follow-ons. Every investor becomes a member of the AI Venture Club, with opportunities to invest in Syndications, learn, and network.

To learn more, click below to review fund materials or connect with a Senior Partner.

Anton Simunovic
Anton Simunovic
Chief Investment Officer, Alumni Ventures.

Anton is the Chief Investment Officer at Alumni Ventures. Anton has over two decades of technology experience as a proven venture capital investor, entrepreneur, and operating executive in companies ranging from startups to Fortune 10 organizations. Anton possesses substantial international experience in Canada, China, Europe, and Israel and has served on the board of directors of more than 20 private and public companies.

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.

Webinar: An Introduction to AV’s Q1 Focused Funds

Wednesday, January 26, 2:00 PM ET
Hear from CEO Mike Collins and CIO Anton Simunovic about the thesis for our Q1 Focused Funds and how AV’s powerful deal sourcing and investing engine builds a portfolio for each with ~20-30 companies, diversified by stage, geography, and lead investor. 

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.

Beyond these criteria, we also take into consideration these factors:
  • We like to invest in companies with strong founders and teams — the earlier the stage, the more important the team. Therefore, founder/market fit is critical and ideally, we like to see previous startup experience and success on management’s resumes. 
  • The AV model is to co-invest behind experienced VCs. Even better, we like to see a strong syndicate of investors who can help shape strategy, products and services, assist in recruiting, and make valuable introductions.
  • We also like companies that are solving difficult problems so there is technical complexity, IP, and the potential to build an engineering headstart if not an outright barrier to entry against competition. Counter-intuitively, the more technical the solution, the more we like to see mixed-DNA on the leadership team.
  • We look for an attractive price and valuation and always aim for pro-rata rights.

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.

Lacey Farrell Johnson
Lacey Farrell Johnson
Managing Partner, Focused Funds

Lacey joined Green D Ventures from CareGroup Investment Office, a $3 billion manager of combined endowment and pension assets. As a member of the investment team, Lacey was responsible for investment sourcing and due diligence. Lacey managed investment opportunities across asset classes and strategies, including venture capital, growth equity, buyout, private credit, and hedge fund vehicles. Previously, she was an Associate at J.P. Morgan Asset Management and an Analyst in the Securities Division of Goldman Sachs. Lacey has a BA in History from Middlebury College and an MBA from Tuck.

Jonathan Mo
Jonathan Mo
Principal, Focused Funds

Jonathan previously invested in frontier tech startups across prior VC roles at 11.2 Capital, Avery Dennison Ventures, and Silicon Valley Bank. He also supported the startup operations and product team at TandemLaunch, a deep tech startup foundry, and has helped build data-centric and automation tools at many of his roles. He studied astrophysics, biology, and political theory at Columbia, biochemistry at NYU, and has conducted research in both the physical and life sciences. He later studied medicine at the National University of Ireland, and game theory and strategy at The London School of Economics.

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.

AI Fund Open Through Q1 2023

Our AI Fund will invest in a diversified portfolio of ~20-30 companies applying AI, machine learning, big data, and related technologies. The fund will be invested over ~12-18 months with a large reserve (~20-25%) for follow-ons. Every investor becomes a member of the AI Venture Club, with opportunities to invest in Syndications, learn, and network.

To learn more, click below to review fund materials or connect with a Senior Partner.

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.

Contact [email protected] for additional information. To see additional risk factors and investment considerations, visit av-funds.com/disclosures.