You ever try building a financial model off an earnings call, then spend the next three hours chasing footnotes like they owe you rent? That’s the grind Daloopa’s founders walked away from, and let’s just say they didn’t leave quietly. They left with an MVP built in a basement, a chip on their shoulder, and a mission to turn chaos into clarity.
Fast forward to 2025, and Daloopa isn’t just parsing data, it’s breaking the ceiling on what institutional finance thought was possible. The New York-based company just locked in a $13 million strategic investment led by Pavilion Capital, bringing total funding to $51 million. Not a bad run for a team that saw the spreadsheet sausage being made and said, “There’s got to be a better way.”
Co-founder and CEO Thomas Li, a former equity research analyst at Point72 and Angelo Gordon, knew the pain firsthand. So he teamed up with Jeremy Huang, an ex-Airbnb engineer, and Daniel Chen, a Microsoft alum, both NYU-trained technologists who don’t just understand code, they understand capital flows. The result? A platform delivering up to 10x more data points per company, each hyperlinked to its original source.
This isn’t about “more data.” Everyone says that. This is about auditable, structured, source-linked data that LLMs like Claude and GPT can chew on without hallucinating. The Model Context Protocol (MCP) lets these models plug into the real financial world, not the fantasy league most platforms are peddling.
The secret sauce? Deep AI / ML built for structured and unstructured disclosures, filings, transcripts, footnotes, and all the other goodies investors avoid reading but can’t afford to ignore. It’s not just automation. It’s precision. Accuracy. Trust.
With offices in NYC, New Delhi, and Rio de Janeiro, Daloopa is going global while staying lethal. Hundreds of hedge funds, mutual funds, PE firms, and corporates are already on board. And now with Pavilion Capital joining forces with Touring Capital, Morgan Stanley, Nexus Venture Partners, and Credit Suisse’s NEXT Investors, this isn’t just a cap table, it’s a signal.
The market for clean, verifiable, AI-ready data is massive. But the bar for trust? Even higher. Daloopa’s not chasing hype. They’re building infrastructure for a future where AI doesn’t just guess, it knows. Because when the model needs to be right, Daloopa’s the source.
