This 11-page pitch deck helped Hum Capital, a fintech using AI to match investors with startups, raise a $9 million Series A
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- Hum Capital is a startup that uses AI to match investors and private companies looking to fundraise.
- The New York-based fintech raised its $9 million Series A on Tuesday.
- This is the 11-page pitch deck the startup used for the round.
Blair Silverberg is no stranger to fundraising.
For six years, Silverberg was a venture capitalist at Draper Fisher Jurvetson and Private Credit Investments making bets on startups.
“I was meeting with thousands of founders in person each year, watching them one at a time go through this friction where they’re meeting a ton of investors, and the investors are all asking the same questions,” Silverberg told Insider.
He switched gears about three years ago, moving to the opposite side of the metaphorical table, to start Hum Capital, which uses artificial intelligence to match investors with startups looking to fundraise.
On Tuesday the New York-based fintech announced its $9 million Series A. The round was led by Future Ventures with participation from Webb Investment Network, Wavemaker Partners, and Partech.
Hum relies on AI to answer common questions among investors and startups
Hum uses artificial intelligence and data integrations to gather answers to common investor questions that are often found within the software logs companies use to run their businesses.
Startups raising money connect their underlying systems to Hum. After analyzing the business, Hum matches the startup with three or four investors on its network.
Hum also uses a bot or web crawler to gather and organize public information about investors on its marketplace, such as portfolio companies and focus areas, Silverberg said. When an investor visits the network, Hum may ask a couple of additional questions to build out a clearer profile, he added.
The goal is for founders to come away from the meetings with term sheets and more control over picking investors, Silverberg said, while investors get personalized deal flow and a streamlined investment decision process.
Beyond the initial match-making, Hum’s investors and startups will typically use the data and analytics dashboard post-investment, Silverberg added, rather than manually filling out spreadsheets and sifting through documents to find answers to specific data-based questions.
“It really just came out of my experience doing that manually as a venture capitalist,” Silverberg said.
Since the beginning of the year, Hum has helped companies raise more than $400 million and has 250 institutional investors on its platform. Hum specializes in companies raising between $1 million and $100 million, Silverberg added.