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Valon Raises $150M for AI-Native Mortgage Servicing Platform

Valon Raises $150M at $2.3B Valuation Valon has raised $150 million in Series D funding at a $2.3 billion valuation. The round doubles the company’s previous valuation. New investor Ribbit The post Valon Raises $150M for AI-Native Mortgage Servicing Platform appeared first on Ventureburn .

Valon Raises $150M for AI-Native Mortgage Servicing Platform

Valon, an AI-native mortgage servicing platform, has secured $150 million in Series D funding, bringing its valuation to $2.3 billion. The investment round doubles the company's previous valuation and was led by new investor Ribbit Capital, alongside existing backers Andreessen Horowitz. The funds will bolster product development and expand Valon's workforce, with new roles opening in New York, San Francisco, and remote locations.

The company aims to transition major mortgage servicers from legacy systems to its ValonOS platform, which consolidates core servicing functions within a single operating system. Valon also provides AI agents for regulated servicing workflows, such as answering homeowner emails, allocating payments, and performing escrow analyses.

The platform is being adopted by major mortgage institutions like ServiceMac, Carrington Mortgage Services, and Rithm Capital's Newrez. ValonOS replaces legacy technology used in traditional mortgage servicing operations and provides a foundation for AI agents that require structured data and clear context to execute controlled actions with reliable audit trails.

Linda Du, Valon's co-founder and President, acknowledges context as a major AI challenge and emphasizes the company's six years of operating a mortgage servicer. Valon's technology is already scaling across more institutions, with one in six outstanding U.S. mortgages projected to use the platform. The funding will support Valon's expansion into other regulated finance sectors, including commercial, personal, auto, and student lending.

Written by urgent.news from Ventureburn's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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