Thomas Li was working at Point72, the hedge fund founded by notorious investor Steve Cohen, when he realized that the financial industry relies heavily on manual data entry processes that can be prone to errors.
“As a buy-side analyst, I felt the pain of manually sourcing and entering data to build and update financial models,” Li told TechCrunch. “It took time away from the more important work of analyzing and making investments.”
After Li met Jeremy Huang, a former software engineer at Airbnb and Meta, and Daniel Chen, a former Microsoft engineer, through connections at New York University (all three are graduates), he decided to work on an automated solution for the Data to try entry challenges.
The three partners launched Daloopa, which uses AI to extract and organize data from financial reports and investor presentations for analysts. Daloopa announced Tuesday that it has raised $18 million in a Series B funding round led by Touring Capital with participation from Morgan Stanley and Nexus Venture Partners.
“Daloopa is an AI-powered historical data infrastructure for analysts,” said Li. “This approach to the data discovery process ensures competitive companies and teams stay one step ahead.”
Daloopa’s customers primarily include hedge funds, private equity firms, mutual funds, and corporate and investment banks, says Li. They use the startup’s tools to create workflows for investment and due diligence research. The AI algorithm-based workflows discover and deliver data to analysts’ financial models, reducing the need to manually copy data.
“Daloopa offers a new way to deliver business-critical data to both the buy and sell sides,” said Li. “The time saved is reinvested in research and analysis, or the time we spend in contact with the customer remain – which helps our customers get a head start in their research process.”
Now I’m a little skeptical as to whether Daloopa’s AI doesn’t make mistakes: After all, no AI system is perfect. Due to the phenomenon known as hallucination, it is not uncommon for AI models to make up facts and figures when summarizing documents and files.
Li did not claim that Daloopa is foolproof. However, he claimed that the platform’s algorithms “continue to improve over time” as they are trained on increasing volumes of financial documents. Mom knows exactly where the data comes from. Li says it’s a trade secret.
“Daloopa has been an AI company since it was founded five years ago, before all the AI hype,” said Li. “We have spent those years training our algorithms and developing AI for financial institutions.”
With the new funding, which brings New York-based Daloopa’s total revenue to $40 million, the company plans to grow its team of approximately 300 employees, strengthen product research and development and expand its customer acquisition efforts.
“Daloopa is an AI-powered solution that has been ahead of the curve and has seen year-on-year growth over the last two years,” he said. “As financial institutions increasingly adopt AI tools, we are very well positioned to be a leader in AI-driven fundamental data.”