Veeam acquires data security company Securiti AI for $1.7bn

In a strategic move to enhance data security and empower customers, Veeam, a data resilience company based in Kirkland, Washington, has announced its acquisition of Securiti AI for approximately $1.725 billion. This agreement, which was made public on Tuesday, combines cash and stock components and is projected to finalize in the first week of December. Founded in 2019 by Rehan Jalil, Securiti AI has established itself as a leader in providing enterprises with a comprehensive command center for managing their data. The company has successfully raised over $156 million in venture capital from notable investors, including Mayfield, General Catalyst, and Cisco Investments. Once the acquisition is complete, Veeam plans to integrate Securiti’s innovative data command center product into its existing suite of offerings, further enhancing its capabilities in data governance and security. Anand Eswaran, CEO of Veeam, emphasized the changing landscape of data management, stating, "We’ve entered a new era for data. It’s no longer just about protecting data from cyber threats and unforeseen disasters; it’s about ensuring that data is identified, governed, and trusted to support AI transparently." Veeam's commitment to growth is apparent, especially following its $2 billion secondary sale in December 2024, which valued the company at $15 billion. Eswaran previously indicated that the company would seek acquisitions that complement its data resilience strategy as part of its 2025 plans. This acquisition comes during a period of significant consolidation within the data industry, as companies look to streamline their data infrastructures to better adopt AI technologies. Notable transactions earlier this year included Databricks' acquisition of Neon for $1 billion and Salesforce's purchase of Informatica for $8 billion. Although such deals have slowed, experts like Sanjeev Mohan, a former Gartner analyst, predict that consolidation will continue as enterprises strive to overcome data fragmentation and inefficiencies in their data stacks.