Blair Silverberg is Capital’s Co-Founder and CEO. Prior to Capital, Blair was a Principal at Draper, Fisher Jurvetson where he specialized in fintech (Prosper and LendKey) and machine learning companies (Nervana Systems, acq. by Intel for $480M). He sourced and managed investments of $22M into four companies generating $103M of realized and unrealized value. Before DFJ, Blair was a product lead at Intuit and co-founded an online tutoring marketplace called TutorCloud.
1. Tell us about your role at Capital?
I am the Founder and CEO. I founded Capital in early 2019 after having been a venture capitalist at Draper Fisher Jurvetson. It was there where I realized just how broken private capital markets were and I and my co-founders created Capital to fix them.
2. Can you tell us your journey into this market?
I was fascinated with the stock market at a young age and got started in investing by using my bar mitzvah money to buy stocks. I earned about $100,000 in the stock market as a teenager, just from being able to get access to that one early infusion of capital.
As a college student, I went to Stanford and studied product design under David Kelly, the founder of Ideo. Starting with conversations that I had with him and with other company founders, I’ve been thinking about improving capital access. I see this as a huge area of opportunity to solve problems, with compounding benefits to society if we can make our capital allocation process more efficient.
From the perspective of a CEO or CFO, you set goals and want to efficiently be able to access financing to achieve them. Access should purely be about whether your goals are achievable – not who you know or how charismatic you are.
3. How do you think technology is upgrading in the financial sector?
The average company generates hundreds of gigabytes of data as it operates and as of 2018, half of these companies were fully cloud-native — meaning that they run their businesses on cloud-connected systems of record which make all of the data that lives inside them available via APIs. Excel was built for a world where companies closed their books quarterly and accountants sat between decision-makers and data.
Today’s companies require distributed computing infrastructure and serious machine learning to make sense of their data and consolidate the data into action-oriented analytics. While these tools have become widely available, company executives do not have the time or resources to build their own analytics suites and investors do not have R&D budgets. By funneling its extensive R&D budget into cutting edge analytics, a Capital-as-a-Service platform like Capital’s can find signal in all of the data companies generate and make that easily available to a company and its investors in the form of analytics and metrics to make better decisions and, over time, build more adaptive, agile businesses.
To put a point on this, today’s private market investors who intermediate over $5T of assets ignore 99.998% of the data available to them when assessing companies because Excel constrains their analysis.
4. How has the application of AI technology empowered the financial ecosystem?
By utilizing AI in place of Excel files, all the signals on a business’s fundamentals are available to the operators and investors in a business.
Smart business people can spend their time responding to the state of the world rather than debating what it may be.
They can see trends in customer behavior or financing options and shift the business to adapt in real time. In this world where reaction time goes from quarterly to daily, businesses lose the static labels of “good” or “bad”. Investors and operators pour their efforts into building the future together as partners rather than counterparties looking to get the best deal out of each other. This expands the pie and focuses the economy on what matters — growth.
5. How does Capital deliver specific insights from a macro-economic lens?
Capital sees thousands of businesses’ performance at the daily transaction level. From this view it makes general observations which are a lot like Google Trends. For example, this sector is growing at an accelerated rate or that sector is highly seasonal or some other sector was surprisingly boosted during the emergence of COVID-19 in March. These general insights help companies to know where they stand and make sense of the data they are seeing in their business. They help them to gauge how economic fluctuations may impact them and ultimately choose what level of risk to take when deciding which investments to make and how to finance them. They also give investors specific frameworks to consider recessions or other economic disruptions which make them more gray, and thus more financeable than most investors would think without that data.
6. What impact is technology having on evaluation of capital efficiency of businesses?
Capital has helped over 1,000 emerging growth companies to understand their capital efficiency and also efficiently access capital from the $5T private capital markets. The Capital Machine crunches an average of 40 gigabytes of data per company providing detailed analytics not possible to generate with Excel. These analytics regularly surprise CEOs and CFOs who are able to cut down on less efficient parts of their businesses in order to plow investment into their efficient cores. These insights and behavioral change tell a clarifying story to investors who are plugged into The Capital Machine themselves and able to quickly invest when they recognize these financeable opportunities. The net result is a market that operates on data and values capital efficiency over charm.
7. Can you explain to us in detail about how The Capital Machine works?
The Capital Machine lets companies unlock direct financing, tailored analytics and recommendations simply by connecting their basic systems of record (Shopify, Quickbooks,etc.) to the platform. Capital pulls tens of GBs of raw data and runs proprietary AI-powered analytics to synthesize this data into detailed cohort projections for sales & marketing, inventory, CapEx, etc. The result is a detailed view of a business attributing revenues to specific types of expenditures which makes it possible to finance these expenditures directly. Traditional venture lenders just look at sponsors so they miss businesses with wonderful economic performance but less sexy sponsors (or even worse from their perspectives – bootstrapped companies). At the end of the day, all that matters is that a business uses capital wisely to grow – this is the only thing that matters and with a detailed picture in hand, investors using The Capital Machine do not have to rely on these crude and lossy proxies which are so common in today’s marketplace.
8. What advice would you like to give to other technology Start Ups?
Develop the right mindset. Building a company is mental warfare and before you embark on the journey, you should be mentally ready to persist through anything that is thrown at you. I have found in my own experience that resetting the way I think about building my business from being focused on success to having fun on a daily basis solving problems has been the key to my grit and determination. Whether you are dealing with daily setbacks – a great recruit goes elsewhere, you miss a product milestone – or corporate near-death – you will only survive if you have the right mindset. If you don’t believe me, watch Revenge of the Electric Car which shows Elon Musk living through the launch of Tesla during the great recession. You can see exactly why he says starting a company is like eating glass and staring into the abyss and you can also see why his persistence has led him to incredible success today.
9. What is the Digital innovation in AI technology, according to you, that will mark 2020?
First, AI is a decades long arc so there will be no silver bullet in 2020 or any other year. With that said, we are in the era of vertical AI. If you are building an AI business, you will see very early on that 80% of your R&D resources go to cleaning and then understanding the data you are working with so that you can feed it into the much-touted algorithms that are constantly improving. Because of this, if you are building a business in a single space, your ability to organize all the data and interpret it with experts can get you to escape velocity in a way that more general approaches to AI cannot. This will be true perhaps for decades – at least until all major sectors have well-organized and standardized data at which point a more generalized AI approach can leverage data across sectors. We are nowhere close to this today.
10. What are the major developments you are planning, in recent time?
2020 was about building The Capital Machine to a point of technical sophistication that it can truly power the complex commercial transactions that have so far required legions of smart humans to intervene. 2021 is about growing its impact throughout the venture debt space and making non-dilutive capital widely available to tech companies which today are remarkably underlevered. More to come so stay tuned!
11. Can you tell us about your team and how it supports you?
In a vertical AI business, the name of the game is synthesizing technologists and non-technical experts. At Capital, we have a 50-50 mix of deep Silicon Valley technology expertise and Wall Street which means great legal and economic minds. We debate often and have come to a remarkable mutual trust and curiosity that lets these two cultures flourish under one roof. In terms of my team day-to-day, I rely heavily on strong leaders of each team. Every project is owned by someone other than me and my job is to facilitate context sharing amongst teams.
12. Can you give us a glance of the applications you use on your phone?
Discord for team chat, The Economist and Feedly for reading and Nest to watch my children during nap time. I could probably delete everything else!