Guy Perelmuter is the founder of GRIDS Capital, a deep tech venture capital firm focusing on artificial intelligence, robotics, life sciences, and technological infrastructure founded in 2016. He earned his Bachelor of Science in Computer Engineering in 1994 and a Master of Science in Electrical Engineering in 1996, both from the Pontifical Catholic University of Rio de Janeiro in Brazil. He specialized in computer vision techniques using artificial intelligence back in the mid 1990’s. In 1997, he was one of the winners of the Brazil Young Scientist Award for the implementation of his solution to produce texts in Braille using dot matrix printers, and he later went on to develop risk analysis and asset allocation systems. His book “Present Future: Business, Science and the Deep Tech Revolution” (Fast Company Press) was selected as a Top Business Book of 2022 by the Next Big Idea Club and won gold medals from both the 2022 Axiom Business Book Awards (Business Technology) and the 2021 Foreword Indies Awards (Science and Technology).
Ananya: How does your experience in direct investing inform how you evaluate potential fund investments?
Guy: Our strategy at GRIDS Capital is based on being able to consistently obtain an efficient risk/return ratio for our investors — in other words, regardless of the macro environment, we want to be in a great position to deliver strong results. By blending allocations in extraordinary deep tech funds with direct investments, we achieve significant diversification in a highly curated list of companies and the possibility to overweight our allocations in specific companies (that are usually sourced from our GPs). Having said that, direct investing brings many benefits to the portfolio and to our firm — there’s a great 2021 blog post by Dave Shekar and Aaron Miller from CF Private Equity that is worth checking out and that I quote below.
First and foremost, direct investing allows us to develop the necessary networks and relationships with top-tier GPs and to identify potential breakout companies. Evaluating and underwriting investments while leveraging the knowledge of industry experts is extremely beneficial — and this experience will consistently provide insights into a fund's qualitative and quantitative skills. Moreover, this process allows us to build our own network of sector experts, that will help us in assessing opportunities in multiple sectors.
The experience of direct investing also provides valuable insights into risk assessment: investing directly in startups brings a fundamentally different risk profile to the table when compared to investing through a VC fund, where the risk is spread across multiple companies. We believe that by balancing both, we can achieve superior results. Our direct investing experience makes it much easier to understand (and evaluate) how GPs approach and manage risk.
Ananya: What are the most important characteristics you look for when evaluating deep tech funds and managers?
Guy: The list is long, and we are permanently striving to improve it and make it as thorough and robust as possible. Broadly speaking, we look at both quantitative and qualitative aspects: it is the combination of both that will ultimately allow us to make an informed decision.
Because deep tech funds are quite unique when it comes to the skillset necessary to outperform the market, we usually will start from the GP’s ability to be problem-oriented (vs solution-oriented), understanding both physical and digital innovation applied to relevant industrial and/or societal challenges (both BCG and MIT have good articles on the topic). Strong networks with universities, research labs, the Government, and relevant industry actors is a critical aspect that we expect deep tech GP’s to constantly maintain and expand. This allows us to better evaluate their ability to identify and support ventures with unique, protected, or hard-to-reproduce technologies.
A strong technical background and the ability to understand one or more sectors is usually important, since many deep tech initiatives are started by PhD’s, post-PhD’s, and professors at universities and involve patents and/or intellectual property that must be properly evaluated. Understanding the potential capital needs of each individual venture is not always simple, but critical when you are an investor seeking to optimize capital usage — and, probably even more important, is the ability to evaluate the founding team’s soft and hard skills.
Each company’s journey is unique, but successful deep tech companies usually are started by deeply technical founders that, at some point, need to partner with professionals with different backgrounds (sales, marketing, business development, etc.). We need to make sure that the GPs surrounding the founders are aware of this and are willing to help them on their journey.
For each individual GP that we evaluate, we will look at aspects like fund size, number of companies per fund, total number of funds under management, team members, prior experience, track record, partnership structure, risk management capabilities, co-investment opportunities, fee structure, ownership, board participation, industry reputation, which VCs they co-invest with, referrals from current and past LPs, referrals from current and past founders, referrals from other GPs, quality of quarterly newsletters and annual meetings.
As I said before, it is the combination of macro/micro and quantitative/qualitative data that will ultimately provide us with the necessary elements to make the best possible decision on behalf of our investors.
Ananya: What is one piece of advice you would give to investors launching sector-focused funds?
Guy: Understand that the best founders in your sector are not only looking for money: they are looking for technical expertise, strong networks within their specific sector, and the ability to leverage relationships and connections for both technical and financial advisory. The adverse selection problem is very real, and you want to position yourself in a way that will make it obvious for great entrepreneurs in your space to call you (vs the other way around).
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