Bedrock Data, a San Mateo, California-based company that provides a platform for data-focused security, governance, and management, has received an investment from Snowflake Ventures.
The amount of the deal was not disclosed.
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The company plans to use the funds to grow its operations and support development efforts.
With this investment, Snowflake customers will gain access to Bedrock Data’s AI-powered data classification and governance tools via Snowflake Horizon, providing a unified view of their data. Bedrock Data also launched a new ArgusAI integration with Snowflake Cortex AI, which gives companies better visibility into AI agents and the data they use, helping them manage generative AI with lower risk and greater confidence.
Snowflake customers will benefit from Bedrock Data’s AI-powered data classification and governance tools via Snowflake Horizon, providing a unified view of their data.
This partnership brings Bedrock Data’s patented Metadata Lake to Snowflake Horizon. The Metadata Lake is a continuously updated knowledge base that maps key details across enterprise data, including sensitivity, lineage, access rights, usage patterns, and business context. It serves as a single source of truth for data sensitivity and risk across the organization, enabling companies to use Snowflake across all workflows, including AI and agent-based applications, without manual tagging.
Bedrock Data gives organizations continuous, large-scale visibility into Snowflake environments and helps secure sensitive data stored there. It can automatically find and classify important data, including PII, PHI, sensitive personal information, intellectual property, and other valuable assets, across structured, semi-structured, and unstructured data. The platform also assigns Impact Scores to schemas and tables based on the amount of sensitive data they contain, helping companies focus on the highest-risk areas first.
By mapping access across users, service accounts, roles, and AI agents, Bedrock Data shows exactly who can access sensitive data in Snowflake. It uses Snowflake’s native tagging features to automatically label data at the database, table, and column levels based on type and sensitivity. The platform also automates access controls and masking policies in Snowflake while keeping the Snowflake Horizon Catalog up to date with real-time sensitivity data.
In addition, Bedrock Data tracks data lineage and actual usage patterns, helping companies see how data moves between Snowflake and other systems and reduce unnecessary access that could increase security risk.
Bedrock Data’s ArgusAI solution now also integrates with Cortex AI, Snowflake’s generative AI service, to inventory and catalog Cortex Agents and map the data they can access through Cortex Search and Cortex Analyst.
As companies adopt AI more quickly, they are facing new data governance challenges. AI results depend on the quality, security, and controls of the underlying data. According to Bedrock Data’s 2025 Enterprise Data Security Confidence Index, 79% of security teams struggle to classify sensitive data used in AI and machine learning systems and only 48% say they are highly confident in their ability to control sensitive data used for AI and ML training. Without large-scale data discovery, classification, and access analysis, companies cannot properly govern the AI systems they deploy, creating regulatory, security, and innovation risks.
“Companies run many of their most important data and AI workloads on Snowflake, where strong governance supports AI adoption,” said Harsha Kapre, Head of Snowflake Ventures. “Bedrock Data’s integrations with Snowflake Horizon and Snowflake Cortex AI help shared customers move faster on AI while maintaining security and compliance.”
“For many large companies, Snowflake stores the data behind their most important decisions. Protecting that data across both traditional analytics and new AI applications is essential for any enterprise AI strategy,” said Bruno Kurtic, CEO and co-founder of Bedrock Data. Snowflake’s investment shows that strong data governance is not optional, but necessary for using AI with confidence. Together, we are giving companies the visibility and control they need to innovate while improving security, governance, and compliance.”
About Bedrock Data
Founded by Bruno Kurtic, Pranava Adduri, and Ganesha Shanmuganathan, Bedrock Data provides continuous, context-aware security and governance for enterprise data across private cloud, IaaS, PaaS, SaaS, and AI environments. Using its patented Metadata Lake and Serverless Outpost architecture, Bedrock Data automatically discovers, classifies, and adds context to data without moving it outside customer boundaries. It’s an open, API-first platform that integrates with existing systems and supports natural-language policy enforcement, AI governance and automated remediation at scale. Leading global companies across technology, finance, healthcare, and biotech rely on Bedrock Data to operationalize data security.
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