Databricks has closed a $5 billion strategic funding round, raising its valuation to $190 billion as the data intelligence company accelerates investment in enterprise AI and autonomous agents. Coatue led the financing alongside Blackstone, MGX, T. Rowe Price and Sixth Street Growth, with participation from a broad group of new and existing investors. The latest valuation represents a dramatic increase from the $62 billion valuation Databricks reached following its $10 billion Series J financing in 2024.
Databricks provides a data intelligence platform that enables organizations to analyze enterprise data, build generative AI applications and deploy AI tools using their own private information. Its technology is used across industries including healthcare and life sciences, financial services and manufacturing, allowing teams to combine data analytics with natural-language AI capabilities. The company is increasingly focused on helping enterprises move beyond conversational AI toward agents capable of executing tasks across business workflows.
The new capital will support further development of three core products: Lakebase, Genie and Unity AI Gateway. Lakebase provides an operational database designed for AI agents, while Genie functions as an AI coworker that can interpret enterprise data and turn it into answers and actions. Unity AI Gateway provides centralized governance, monitoring and cost controls for organizations deploying multiple AI models and applications. Together, the technologies form part of Databricks' strategy to provide the data, context and governance infrastructure needed to deploy enterprise AI agents at scale.
The funding comes amid strong growth for Databricks, which reports more than 80% year-over-year growth and annualized revenue exceeding $7 billion. The company has also generated positive adjusted free cash flow over the past year and operates more than 30 offices worldwide. The latest financing underscores investor confidence in enterprise AI infrastructure as businesses increasingly seek platforms capable of connecting proprietary data with autonomous AI systems while maintaining governance and controlling costs.
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