Snowflake backs Bedrock Data in AI governance push

Snowflake Ventures has made a strategic investment in Bedrock Data and expanded the technical integration between Bedrock's data governance tools and Snowflake's Horizon and Cortex AI products.

The move more closely connects Bedrock Data's classification, entitlement analysis and masking capabilities with Snowflake's AI Data Cloud, as companies face greater scrutiny over how sensitive information is used in analytics and generative AI systems.

The integration is now available for data discovery, classification, entitlement analysis and native masking invocation. Bedrock Data also said its ArgusAI product now integrates with Snowflake Cortex AI to inventory Cortex Agents and map the data they can access through Cortex Search and Cortex Analyst.

The announcement reflects growing demand for governance tools that can track how corporate data is classified, who can access it and how it is used as businesses expand AI projects. Snowflake and Bedrock are positioning the tie-up around that need, particularly for organisations managing large, complex data estates.

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, while 48% say they have high confidence in controlling sensitive data used for AI and machine learning training.

Deeper Integration

Under the partnership, Bedrock Data's Metadata Lake will feed information into Snowflake Horizon, giving customers a unified view of data sensitivity and related risk context across their environments. The Metadata Lake is described as a continuously updated graph knowledge base covering sensitivity, lineage, entitlements, access patterns and business context.

This information is intended to help organisations identify sensitive data across structured, semi-structured and unstructured datasets stored in Snowflake. The platform can classify data including personally identifiable information, protected health information, intellectual property and other sensitive assets.

It also assigns impact scores to schemas and tables based on the amount and sensitivity of the data they contain, helping users decide where to apply security controls first.

Another part of the integration focuses on access mapping. Bedrock's platform maps entitlements across users, service accounts, roles and AI agents, allowing organisations to see who has access to sensitive information inside Snowflake environments.

It also uses Snowflake's native tagging features to label data at the database, table and column level based on type and sensitivity. The platform automates masking policies and access controls within Snowflake, while updating the Snowflake Horizon Catalog with real-time sensitivity information.

AI Oversight

The Cortex AI integration extends that approach to generative AI services. ArgusAI can catalogue Cortex Agents and show what data they can access through Cortex Search and Cortex Analyst.

This addresses a newer governance question emerging from enterprise AI deployments: not only where sensitive data resides, but how autonomous or semi-autonomous AI tools can reach and use it.

Harsha Kapre, Head of Snowflake Ventures, described governance as central to broader AI adoption on the platform.

"Enterprises run their most critical data and AI workloads on Snowflake, where strong governance enables AI adoption. Bedrock Data's integrations with Snowflake Horizon and Snowflake Cortex AI help joint customers accelerate AI initiatives while maintaining security and compliance."

For Bedrock Data, the investment also provides backing from a strategic platform partner at a time when governance vendors are trying to prove their relevance in AI spending cycles. Buyers are increasingly looking for tools that fit into existing cloud and data stacks rather than stand-alone products that require separate workflows.

Bruno Kurtic, CEO and Co-founder of Bedrock Data, linked the partnership to that broader shift in enterprise priorities.

"For many large enterprises, Snowflake is home to the data that drives their most important decisions. Securing that data, across both traditional analytics workloads and emerging AI applications, is a foundational requirement for any enterprise AI strategy.

"Snowflake's investment affirms that data-centric governance is not a nice-to-have - it is a prerequisite for deploying AI with confidence. Together, we are giving enterprises the data visibility and control they need to innovate while improving security, governance and compliance," said Kurtic.

The partnership adds to a broader push across the data infrastructure market to tie governance more closely to AI deployment, especially as companies seek clearer oversight of data lineage, access rights and model inputs. The combined offering is aimed at helping Snowflake customers govern both analytics workloads and emerging AI and agent-based applications within the same environment.