Databricks acquires two startups for new AI security product

Databricks acquired two startups — Antimatter and SiftD.ai — to create its own product in the field of artificial intelligence security. Both deals were closed using funds from a record-breaking investment round: at the end of 2024, the company raised $5 billion, which was one of the largest rounds in the history of enterprise software.

Databricks is one of the key platforms for data management and machine learning in the enterprise segment. The company built its business on the concept of the 'lakehouse': a unified architecture that combines the capabilities of a data warehouse and a data lake. The platform is used by thousands of companies around the world, including hundreds from the Fortune 500 list.

Databricks' annual revenue exceeds $1.6 billion, and its latest valuation is over $60 billion — making it one of the most valuable non-public technology businesses in the world. Antimatter specialized in protecting data when it is shared between organizations.

The startup developed encrypted enclave technology: it allows multiple companies to work with sensitive data together — for example, to train AI models — without revealing the underlying data to each other or to third parties. This challenge is becoming increasingly acute as enterprises build RAG systems and AI agents that have direct access to confidential corporate knowledge bases. SiftD.

ai addressed a related problem: detecting unauthorized data use and data leaks in AI systems. As language models are integrated into corporate workflows, companies face new threats — from prompt injection attacks to inadvertent disclosure of confidential data through LLM interfaces. Traditional cybersecurity tools were developed before the era of generative AI and cannot handle these specific threat vectors.

The AI security market is experiencing rapid growth. According to various estimates, by the end of the decade it will reach tens of billions of dollars. Databricks, as a company that directly manages data for thousands of large clients, is naturally positioned to offer protection — not only at the storage level but also in the AI application layer built on top of it.

Acquiring ready-made startups instead of developing in-house allows Databricks to reduce time to market and immediately gain teams with specialized expertise. This fits into Databricks' broader M&A strategy: following the record-breaking round, it is sequentially acquiring startups in generative AI, data management, and now security. What is happening reflects an important trend: large platform players are consolidating niche AI security specialists, preventing independent leaders from forming in this market.

For startups in this field, the window of opportunity is narrowing — the next 12–18 months will likely determine who remains an independent company and who becomes part of tech giants.