Concentric AI Expands Data Security Ambitions With Swift Security, Acante Acquisitions
Data security governance provider Concentric AI announced its acquisition of Swift Security and Acante, two AI-driven security startups, in a move Concentric AI founder and CEO Karthik Krishnan hopes will reshape enterprise data protection. The deal, unveiled yesterday, Krishnan said positions Concentric AI as the first vendor to unify data security posture management (DSPM), data loss prevention (DLP) and generative AI (GenAI) governance across structured, unstructured, and semi-structured data, spanning both cloud and on-premises environments.
Each of these data security segments is experiencing significant growth. For instance, the DSPM for the AI market is growing rapidly, with market research firm Frost & Sullivan predicting an annual expansion of 37% through 2029. These tools help organizations discover, classify and secure data across multi-cloud and hybrid environments where AI applications operate.
Market and Markets estimates that the MLOps market will reach approximately $2 billion in 2024 and project it to reach $17 billion by 2030, growing at a 41% annual rate. MLOps platforms include critical data management capabilities for AI model development, deployment and monitoring. The AI governance market, valued at $891 million in 2024, is expected to grow at a 45% annual rate, according to Market and Markets, reaching $6 billion by 2029. This encompasses policies, tools and frameworks for managing data throughout the AI lifecycle.
With these acquisitions, Krishnan told Security Boulevard, Concentric AI’s Semantic Intelligence platform now promises end-to-end protection for enterprise data at rest, in motion, and use. The platform extends from safeguarding sensitive data in GenAI assistants, such as Microsoft Copilot, to monitoring and preventing data exfiltration via public GenAI tools, including ChatGPT and Perplexity. It also addresses the growing challenge of “shadow GenAI”—unauthorized or unmonitored use of generative AI applications within organizations.
Swift Security’s technology enables Concentric AI to detect when employees interact with public GenAI apps and enforce data security oversight, including monitoring the flow of personally identifiable information (PII), payment card data, protected health information (PHI), intellectual property and financial records. Security teams can now make granular decisions to allow, mask, or block sensitive data uploads to these platforms, closing a critical gap in oversight as GenAI adoption accelerates.
Acante’s platform, meanwhile, empowers security teams to curate datasets used for training AI/ML models or proprietary GenAI applications, ensuring sensitive information is excluded, redacted, or encrypted before model development. This capability is becoming increasingly crucial as organizations navigate privacy and compliance risks while investing in AI-powered business processes.
Regulatory Winds Shift: Senate Removes AI Moratorium
Concentric AI’s move comes as the U.S. regulatory environment for artificial intelligence appears in flux. In a near-unanimous 99-1 vote, the U.S. Senate on Tuesday struck down a proposed 10-year federal moratorium that would have prevented states from enacting their own AI regulations. The move signals an era of state-level oversight, ending what Big Tech had hoped would be a decade of regulatory uniformity and instead opening the door to a potential patchwork of local laws governing AI use, privacy and safety.
This development is expected to increase the complexity of compliance for enterprises deploying AI-powered tools, further emphasizing the importance of platforms that can provide granular, context-driven data governance and security across diverse environments.
Concentric AI’s expanded platform arrives at a critical time, as many organizations face mounting pressure to gain efficiencies from AI while also safeguarding sensitive data and navigating evolving regulations.
“For us, this is a foundational aspect of an enterprise’s security infrastructure,” said Krishnan. “There wasn’t any one thing that was helping customers discover, monitor and protect data at scale and efficiently.”
