Sentra, a startup established by a former Israeli Military Intelligence colonel, has successfully raised $150 million in funding aimed at enhancing the understanding and management of data that artificial intelligence (AI) models and agents have access to. This funding signals a significant advancement in the company’s efforts to address challenges posed by AI, particularly in data security and governance.

This latest funding round, led by Capital One Ventures, is part of Sentra’s Series C financing and is designed to broaden the company’s data protection capabilities by integrating data loss protection into a more comprehensive data security platform. According to Yoav Regev, co-founder and CEO of Sentra, this investment will also facilitate advancements in AI governance and agentic AI capabilities, while also reinforcing identity and access controls.

Regev stated, “What we observed over the last two years is that AI presents a significant data challenge. These challenges cannot be resolved without addressing the underlying data effectively.” He stressed the emergence of what he terms the “agentic era,” predicting a rapid expansion in this field over the coming years. In response to a growing market demand, Sentra aims to position itself as a leader in ensuring both data safety and accessibility as organizations increasingly adopt AI technologies.

Since its founding in 2021, Sentra has expanded its workforce to 210 employees and, cumulatively, raised $253 million across four funding rounds. The company saw significant engagement in its previous $50 million Series B funding round led by Key1 Capital in April 2025. Regev’s background includes extensive experience in Israel’s Unit 8200, the military’s elite intelligence corps, marking him as a formidable leader in the tech and cybersecurity space.

Equipping Organizations for AI Adoption

Recognizing a market trend, customers increasingly prefer an integrated end-to-end data security platform that goes beyond isolated capabilities, which aligns with Regev’s vision for Sentra. He noted that decisions concerning data loss protection (DLP) are substantiated when they consider vital contextual factors such as data type, location, and accessibility. “A holistic approach is necessary,” Regev emphasized, explaining that effective solutions must integrate DLP, data security posture management (DSPM), AI security, and identity management.

One of Sentra’s strategic focuses is improving identity management, which Regev believes is crucial for establishing an access intelligence layer connecting human and non-human identities, including AI agents. This advancement could allow for adaptive permissions that ensure agents have access limited to specifics required for their functions. Regev articulated, “We will bridge the gap between these identities, focusing primarily on the non-human ones, to enable on-demand permissions and access to data.”

Currently, Sentra aids organizations in their AI adoption journeys by pinpointing sensitive data and mitigating the risks of unauthorized exposure or access. Through innovative tools, the company addresses issues such as data hygiene and excessive permissions within AI workflows. “The objective is to prevent sensitive data from being improperly introduced to AI models while also ensuring the right data is accessible to the right individuals,” Regev stated.

DSPM, Data Discovery, and Emerging Use Cases

Sentra is broadening its initiatives toward AI governance and agentic AI security, particularly focusing on identifying existing models and agents and the data they can access. Such a focus could expand Sentra’s clientele beyond Chief Information Security Officers (CISOs) to also include Chief Information Officers (CIOs) and Chief Data Officers (CDOs). Regev characterized this emerging landscape where data, security, and technology leaders increasingly share accountability for AI governance.

He noted, “CIOs, CDOs, and CISOs are developing a mutual understanding of the critical role data plays across various aspects of an organization.” To support emerging use cases, continued investment in fundamental DSPM and discovery capabilities is essential, according to Regev. He highlighted priorities such as enhancing data classification, expanding coverage, boosting performance, and refining the identification of data correlations.

Regev concluded, emphasizing the necessity of foundational data management, “To effectively address these challenges, organizations need a robust engine for finding, classifying, and contextualizing data access alongside associated identities.” He underscored Sentra’s distinctive advantage in its capacity to interlink AI security and DLP with an in-depth comprehension of organizational data. Regev asserts that this allows Sentra to compete effectively against larger rivals like Proofpoint and Cyera, leveraging its superior technology, customer environment data retention capabilities, operational cost efficiency, and classification precision. “Many other startups target specific functionalities. While some perform excellently, connecting these features to actual data assets is a significant challenge that we address uniquely,” he stated.