Bedrock Data, a provider of data-centric security, governance, and management solutions, has announced a strategic investment from Snowflake Ventures. The partnership includes deeper integration with Snowflake’s AI Data Cloud and a joint go-to-market initiative aimed at strengthening data governance for enterprises adopting AI.

As part of the collaboration, Bedrock Data’s AI-powered classification and governance capabilities will be integrated into Snowflake Horizon, enabling organizations to gain a unified and comprehensive view of their data environments. In addition, Bedrock Data has introduced an enhanced integration between its Argus AI solution and Snowflake Cortex AI, providing greater visibility into AI agents and the data they interact with. This capability helps enterprises better control generative AI usage while minimizing risk.

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Harsha Kapre, Head of Snowflake Ventures, emphasized that strong governance is essential for scaling AI initiatives. He noted that Bedrock Data’s integration with Snowflake’s ecosystem allows organizations to accelerate innovation while maintaining security and regulatory compliance. As enterprises rapidly expand their use of AI and machine learning, managing and securing underlying data has become increasingly complex. According to Bedrock Data’s 2025 Enterprise Data Security Confidence Index, a majority of security teams struggle to identify and classify sensitive data used in AI systems, and fewer than half feel confident in their ability to control it. Without large-scale data discovery, classification, and access analysis, organizations risk exposing sensitive information and facing compliance challenges. These gaps can hinder innovation and increase exposure to cyber threats.

Bruno Kurtic, CEO and co-founder of Bedrock Data, highlighted that for many enterprises, Snowflake serves as the foundation for critical data and AI workloads. He stated that effective governance is no longer optional but essential for deploying AI securely and responsibly. A key component of the partnership is Bedrock Data’s patented Metadata Lake, a continuously updated knowledge graph that maps data sensitivity, lineage, access rights, and usage patterns across the enterprise. Integrated with Snowflake Horizon, it provides a centralized source of truth for understanding data risk and context. This capability enables organizations to adopt AI-driven workflows without relying on manual data tagging, improving both efficiency and accuracy.

Bedrock Data’s platform delivers continuous visibility across Snowflake environments, automatically identifying and classifying sensitive data such as personally identifiable information (PII), protected health information (PHI), and intellectual property. It supports structured, semi-structured, and unstructured datasets at scale. The platform assigns impact scores to data assets based on sensitivity and volume, helping organizations prioritize high-risk areas. It also maps access permissions across users, service accounts, roles, and AI agents, providing clear insights into who can access critical data.

By leveraging Snowflake’s native tagging capabilities, Bedrock Data automates labeling at multiple levels including databases, tables, and columns and enforces access controls and masking policies directly within the environment. Real-time updates ensure that Snowflake Horizon’s catalog remains aligned with current data sensitivity. Additionally, the platform tracks data lineage and usage patterns, allowing organizations to visualize how data flows across systems and eliminate unnecessary access, thereby reducing the overall attack surface.

Bedrock Data’s ArgusAI solution now integrates with Snowflake Cortex AI to provide deeper oversight of generative AI usage. It catalogs AI agents and maps the data they can access through services like Cortex Search and Cortex Analyst, enabling organizations to govern AI-driven processes more effectively Through this investment and expanded integration, Bedrock Data and Snowflake aim to help enterprises balance innovation with security. By improving visibility, automating governance, and strengthening data controls, the partnership empowers organizations to adopt AI with greater confidence while maintaining compliance and reducing risk.

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