Sentra raises $150M to build data security platform for AI agents

Securing the agentic era

Sentra recently secured $150 million in Series C funding to build a comprehensive data security platform. This investment, led by Capital One Ventures, follows a $50 million Series B round in April 2025. The company intends to use the capital to develop tools that help organizations manage the risks associated with adopting artificial intelligence.

The startup's core mission is to monitor and regulate the information that AI models and agents can reach. CEO Yoav Regev notes that the 'agentic era'—the period where AI can perform tasks autonomously—is just beginning. He believes that the explosion of these agents in the coming years will create significant challenges for how companies protect their information.

To address these challenges, Sentra is moving beyond isolated security features to create an end-to-end platform. The company wants to integrate data loss protection (DLP), data security posture management (DSPM), and identity controls. By combining these elements, Sentra aims to provide a unified way for companies to govern how AI interacts with their internal assets.

Connecting identities to data

A major part of Sentra's strategy involves mapping both human and non-human identities to specific data sets. Non-human identities include the AI agents that perform automated tasks for businesses. Regev explains that the goal is to connect these identities directly to the data they need to function.

This connection allows for what the company calls adaptive, time-limited permissions. Instead of giving an AI agent permanent access to a database, the system can grant access only for a specific task. This ensures that agents receive the minimum amount of information required to complete a job, reducing the risk of broad data exposure.

The company argues that current infrastructure often lacks this level of context. Regev stated, "You cannot follow the agents," to explain why unique identities are needed for on-demand access. By focusing on these dynamic permissions, Sentra hopes to solve the specific security problems created by autonomous AI workflows.

Data discovery as the foundation

Sentra's technology relies heavily on its core capabilities in data discovery and classification. For a security platform to work, it must first be able to find where sensitive data lives and what it actually contains. The company plans to continue investing in these 'basics' to improve classification accuracy and expand its data coverage.

The platform provides context by identifying what the data is, where it resides, and who is authorized to see it. This information is used to make more effective data loss protection decisions. Rather than just looking at endpoints or emails in isolation, the system uses the broader context of the data to determine if a move is safe.

Regev compares the importance of these core capabilities to the engine of a car. He argues that while many startups offer specific features, they often fail to connect those features to the actual data assets. Sentra differentiates itself by ensuring that every security measure is rooted in a deep understanding of the organization's data layer.

Expanding the buyer group

By focusing on the intersection of data, security, and AI, Sentra is expanding its target market. While the company has traditionally served Chief Information Security Officers (CISOs), it now expects to work more closely with Chief Information Officers (CIOs) and Chief Data Officers (CDOs). These leaders are increasingly sharing the responsibility for AI governance and data management.

The company currently helps customers prepare for AI by identifying sensitive information that might be exposed to the wrong models. For example, it helps prevent sensitive data from being pushed to public models or being retrieved by the wrong person through tools like Gemini or Copilot. These use cases include data hygiene and addressing excessive permissions in current AI workflows.

Looking ahead, Sentra intends to strengthen its ability to associate access with identity information. The company aims to compete with larger rivals by keeping customer data within the customer's own environment. By focusing on operational costs and classification accuracy, Sentra seeks to provide a more integrated solution than competitors who may only offer specific features.