Exclusive: AI financial platform Rowspace raises $50 million led by Sequoia to help investment firms take on messy data

Fortune

by Leo Schwartz

February 25, 2026

AI-Generated Deep Dive Summary

Rowspace, an AI-powered financial platform, has raised $50 million in funding led by Sequoia Capital, with participation from Emergence Capital and others. Founded by Michael Manapat, former CTO of Notion, and Yibo Ling, former director at Uber and Binance, the platform aims to address a common challenge faced by investment firms: managing fragmented data for decision-making. The idea was inspired by the limitations of AI tools like ChatGPT in handling structured and unstructured financial data effectively. Rowspace integrates all types of institutional data—whether from documents, accounting systems, or presentations—and uses advanced reasoning to help private equity firms, hedge funds, and other financial institutions generate actionable insights for capital allocation and operational efficiency. The platform's unique approach differs from consumer tools like Claude Cowork by focusing on deeper analysis rather than surface-level tasks. For instance, Rowspace doesn't take possession of a firm's data; instead, it processes information within the client’s own cloud systems, ensuring security and compliance. This allows the platform to identify patterns and details that might be missed by more general-purpose AI tools like Anthropic. While foundation models excel at tasks like formatting presentations or financial modeling, Rowspace targets specific industry needs, offering tailored solutions for finance professionals. The significance of this innovation lies in its ability to bridge the gap between generic AI capabilities and the specialized requirements of the financial sector. As Alfred Lin of Sequoia Capital highlights, Rowspace exemplifies how niche applications can thrive alongside broader AI advancements. By emphasizing data compilation, synthesis, and secure processing, the platform provides a strategic advantage for firms looking to leverage AI without compromising on accuracy or depth.

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Originally published on Fortune on 2/25/2026