The redesign process is messy. Many experiments will not work. So, how can we generate attractive returns by capitalizing such a messy process?

At Intrepid Fund 1, we focus on three key pillars to optimize our risk-adjusted return:

1. Demonstrated unit economics

Even though we are focused on opportunities enabled by technological advance, we typically do not underwrite core technology risk. Seed and Series A investors do that. As a growth equity investor, Intrepid deploys capital to companies that have already developed their core technology and implemented it with a few initial customers.

Potential portfolio companies typically have at least $10M in annual recurring revenue before we invest. We measure the unit economics of their solution. How much does it improve the quality or quantity of outputs or reduce the cost of inputs? How does that vary across different customer types? In essence, what are the productivity gains their solution delivers to customers. When real productivity gains are demonstrably high, then the growth potential is great. That's when we invest. 

2. Capability to scale

In Fund 1, we are focused on companies based in Canada and the United Kingdom (UK) that are ready to scale to the US market. We're especially focused on Canadian and UK companies for two reasons: 1) the supply of growth equity capital in these countries is low relative to demand (due to historical strengths in research and engineering, these two countries have a disproportionately high level of AI-related startups and thus demand for capital); and 2) Intrepid partners have strong relationships with founders and other network participants in these countries. We are focused on companies with solutions that will scale well in the US market because that market is large and quick to adopt new solutions relative to other markets.  

3. Vision to transform

Many AI-based products are point solutions. Point solutions can be implemented without disrupting the customer's existing operations. Consider navigational AIs like Waze or Google Maps. When these were first invented, they could have been brought to market by licensing the technology to taxi companies. That type of implementation would be a point solution. It would have increased the productivity of taxi drivers without requiring any significant process changes to the taxi industry. Alternatively, with a fully automated navigational AI, people who have never before visited a city can navigate it as well as a professional driver. That enabled the creation of companies like Uber and Lyft. None of the ride-sharing companies could exist without navigational AIs.

Before Uber, there were approximately 200,000 professional limousine and taxi drivers in the US. Today, about four million people drive for Uber in the US. If the average value of a car they drive is $25,000, then this unlocked $100 billion in underutilized capital assets that were otherwise sitting in people’s garages or car parks. These companies transformed the transportation industry. Uber, Lyft, and the others like them represent a system-level solution in contrast to a point solution.

Intrepid focuses on companies that have short-term strategies predicated on point solutions for quick market entry and long-term strategies predicated on system-level transformations that will deliver much greater productivity gains and thus returns. We describe this in Power & Prediction, coauthored by one of our partners.

Advances in AI will precipitate a transformation of the means of production and distribution across the global economy. Intrepid is designed to specialize in the capitalization of this transformation.

If you have a super power that is aligned with our mission and you are keen to explore joining us, then please reach out.