Artificial Intelligence: How CrowdSmart’s Predictive AI Improves VC Investments
Kim Polese (pictured above) is co-founder and chairman of CrowdSmart.
CrowdSmart’s Cyrus is a software-as-a-service (SaaS) platform that uses AI and collective intelligence to better predict the likely result of an investment. Speaking to Barron’s in a panel interview, Polese provided insights on how the platform improved due diligence on a proposed investment. It more accurately predicted the investment outcome, reduced bias, and democratized VC funding. (Barron’s)
How Cyrus works
CrowdSmart’s Cyrus platform screens promising investments for review by a collective team of 25 or more experts and investors.
The platform suggests a team from its panel to invite for an evaluation of the investment. The evaluation team collaborates with the start-up and analyses aspects of the investment. For this, they get access to the start-up’s diligence room and study product performance, financial projections, and videos from the founders of the start-up. The entire process is anonymous, virtual, and remote, yet could take as much as a couple of weeks.
In the next stage, the experts answer questions to form an impression of the likely return from the investment.
Discussions amongst the experts and investors, their individual reflections on the investment, and reactions to each other’s observations are all captured by Cyrus. It is able to formulate the key investment themes and their influence on the investment.
Cyrus also absorbs all the exchange of information in the interactions and brainstorming between the evaluation team and the start-up.
CrowdSmart’s proprietary AI system then processes the data generated during this collective due diligence. This could be either numerical or in a natural language form.
It is then able to determine whether the investment will be successful by transforming the insights into a quantitative score.
“When we’re talking about using collective intelligence, augmented collective intelligence, what we’re really talking about is using a combination of human and machine intelligence to improve the way that diligence is done,” Polese said on the panel.
Reduction in bias
The system is designed to reduce ingrained bias. The venture capital funding business rests primarily on the pillars of relationships and networking. As a result, founders without connections often lost out on funding opportunities. This also applied to women founders.
In initial tests of the CrowdSmart system, Polese found that women were founders or leaders at 42% of the highest-scoring companies.
Because the evaluation discussions are anonymous and the results are quantified by a machine, even a start-up without connections could nevertheless come up as a worthy candidate for funding.
CrowdSmart’s platform can be used for evaluating start-ups, higher stage companies, even those mulling public offerings, and M&A.
Image of Kim Polese: JD Lasica/Flickr
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