Daloopa

Daloopa is a financial technology company that specializes in providing AI-driven data extraction and modeling solutions for investment professionals. Founded in 2019 by Thomas Li, Daniel Chen, and Jeremy Huang, the company addresses the critical inefficiencies inherent in manual data entry and financial modeling. By leveraging advanced artificial intelligence and machine learning technologies, Daloopa automates the extraction of detailed financial data from public filings, including 10-Ks, 10-Qs, and earnings transcripts. This automation allows buy-side analysts, hedge funds, and investment banks to bypass the tedious and error-prone process of manual data collection, thereby freeing up valuable time for higher-level analysis and strategic decision-making.

The company's platform is distinguished by its focus on accuracy, speed, and auditability. Daloopa delivers historical datasets with 99.9% accuracy, covering over 5,000 public companies globally. A key feature of their offering is the ability to provide fully auditable data; every data point within their models is hyperlinked directly to the original source document, ensuring transparency and trust. Their technology integrates seamlessly into existing workflows, most notably through a robust Excel add-in that updates financial models with a single click during earnings seasons. Daloopa has also established strategic partnerships with leading AI firms like Anthropic to integrate Large Language Models (LLMs) into financial workflows, further enhancing the depth and capability of their research tools. Headquartered in New York, with significant operations in India, Daloopa serves a diverse client base that includes some of the world's largest and most demanding financial institutions.