Bedrock Data names AWS and Snowflake Data Governance Veteran Sanjay Srivastava VP of Product. Updated Oct 6, 2026 SAN MATEO, Calif.-(BUSINESS WIRE)-Oct 6, 2026- Bedrock Data, the data security and AI governance platform, today announced that Sanjay Srivastava has joined as Vice President of Product. Srivastava joins from Snowflake, where he led Data Sharing and Collaboration, one of the company's four core product pillars. Before that, he owned AWS Lake Formation, the governance platform at the center of AWS's analytics services. At Bedrock Data, he will lead product strategy and the product management team. AWS and Snowflake Data Governance Veteran Sanjay Srivastava joins Bedrock Data as VP of Product. At Bedrock Data, Srivastava will lead the product that makes data context the foundation for enterprise data security and safe AI adoption. Srivastava has worked on both sides of the problem enterprises now face with AI. At AWS, he built the controls that decide who can access data in the enterprise data lake. At Snowflake, he built the platform enterprises use to share data across teams, partners and clouds, and shipped AI products that put that data to work. That combination maps directly to the question every security team asks before approving an AI rollout: what data is this, is it sensitive and who or what can access it? "AI only creates value when it runs on an enterprise's most proprietary and differentiated data. The job is to enable that access safely, and that requires knowing what the data is, how sensitive it is and who and what can reach it," said Bruno Kurtic, CEO and co-founder of Bedrock Data. "Sanjay built data governance at AWS and data sharing at Snowflake, both at enterprise scale. He understands the teams that protect data and the teams that build on it." At AWS, Srivastava was Principal Product Manager for Lake Formation, the data lake management and governance service used by thousands of enterprises. He led the design and delivery of tag-based access control, cross-account data sharing and enterprise identity integration. At Snowflake, as Director of Product Management for Data Sharing and Collaboration, he built and led a team of senior product managers. He launched an internal marketplace that gives large enterprises visibility into their own data assets across business units, and built production agentic skills on Snowflake Cortex used by enterprise customers. He holds patents in high-performance data sharing and earlier built machine learning products at Conviva and Noosh. At Bedrock Data, Srivastava will own product strategy and the roadmap as the company makes data context the control point for enterprise AI. As AI agents take on more of the work inside the enterprise, every decision they make depends on knowing what the data is, who and what can access it, whether it is at risk and where it came from. Srivastava will lead the expansion of the Bedrock Data platform and the Metadata Lake engine that provides that context, so security, data and AI teams can govern every AI system from one shared understanding of their data. "Every enterprise is deciding right now how much of its data AI can touch, and most are deciding blind," said Srivastava. "Bedrock Data's Metadata Lake gives them the context to decide with confidence. I came here to build on that foundation and take it to every AI system they deploy." Srivastava joins as enterprises scale AI agents across the business. In September, Bedrock Data brought its data-aware policy enforcement to NVIDIA OpenShell, the open source agent runtime. The company is backed by a $25 million Series A led by Greylock Partners and strategic investment from Snowflake Ventures. Additional Resources About Bedrock Data Bedrock Data is a data security and AI governance platform built on an enterprise knowledge graph of the company's data: what it is, where it lives, where it came from, who can access it and how it is used. Bedrock Data builds and maintains that graph, its patented Metadata Lake, by discovering and classifying data in place across cloud, SaaS, AI and on-premises environments at petabyte scale, without moving data outside customer boundaries. Its open, API-first design delivers those facts to the tools already in the enterprise stack and makes them the basis for policy enforcement, AI governance and automated remediation. Security, data, infrastructure and AI leaders in technology, finance, healthcare and biotech rely on Bedrock Data to secure their data and accelerate AI without increasing risk. Learn more at bedrockdata.ai. Bhava Communications for Bedrock Data [email protected] KEYWORD: UNITED STATES NORTH AMERICA CALIFORNIA INDUSTRY KEYWORD: PROFESSIONAL SERVICES DATA MANAGEMENT SECURITY DATA ANALYTICS TECHNOLOGY SOFTWARE ARTIFICIAL INTELLIGENCE PUB: 10/06/2026 09:00 AM/DISC: 10/06/2026 09:03 AM

Bedrock Data adds Agent DLP to NVIDIA OpenShell for AI Agent security. Bedrock Data adds Agent DLP to NVIDIA OpenShell, bringing data-aware runtime controls to autonomous AI agents handling enterprise data. Priyanshi Kharwade. Last updated on: Sep. 29, 2026 Sept. 28, 2026 - Bedrock Data has integrated its Agent DLP technology with NVIDIA OpenShell, adding data-aware policy checks to a runtime designed to control how autonomous AI agents interact with enterprise systems. Announced Sept. 28, 2026, the integration is available to Bedrock Data customers through OpenShell's Supervisor Middleware. Key facts. * Bedrock Data announced the NVIDIA OpenShell integration on Sept. 28, 2026. * Agent DLP evaluates enterprise data context before OpenShell enforces an agent action. * The integration is delivered through OpenShell Supervisor Middleware. * NVIDIA OpenShell provides sandboxed controls over network, filesystem, process and credential activity. * Customers can initially use an observe-only mode before enabling enforcement. * The launch comes alongside NVIDIA's broader Open Agent Safety Platform initiative. According to the announcement, Bedrock evaluates the data involved in an agent request while OpenShell provides the runtime enforcement mechanism. The development comes as enterprises give AI agents greater access to databases, APIs, files, code and business applications. That creates a security issue: an agent may be authorized to perform an action while still handling information that should not be moved to a particular destination. What Bedrock Data adds to NVIDIA OpenShell. NVIDIA OpenShell is an open-source runtime that places AI agents inside isolated environments and applies security policies across filesystem, process and network activity. The NVIDIA OpenShell documentation describes a runtime architecture built around sandboxing and policy controls designed to restrict how agents interact with systems outside their execution environment. Bedrock Data adds information about the data itself to that decision process. Its Agent DLP technology evaluates an agent request against enterprise data policies and returns a decision that OpenShell can enforce. For CISOs, the distinction is important. Conventional permissions determine whether an agent is authorized to access a resource. The Bedrock approach attempts to determine whether the specific information involved in that authorized action should be allowed to move. A permitted database operation, for example, could still be restricted if the underlying data is classified as sensitive and the destination violates enterprise policy. NVIDIA broadens its AI agent security push. The integration arrives as NVIDIA expands its broader approach to AI-agent security. The company announced the NVIDIA Open Agent Safety Platform on Sept. 28, positioning OpenShell as part of a wider architecture for monitoring and controlling autonomous agents. NVIDIA said more than 100 organizations are working with technologies around the platform, including Anthropic, Cisco, CrowdStrike, Microsoft, Palo Alto Networks, Salesforce, SAP, ServiceNow and JPMorganChase. For NVIDIA, the strategy extends security beyond controls embedded inside individual AI models. OpenShell instead acts as an external runtime boundary where agent activity can be governed while tasks are being executed. For cybersecurity companies such as Bedrock Data, that creates another integration point for data protection and AI-governance technologies. What CISOs need to evaluate. Enterprise security leaders are increasingly being asked to govern AI agents capable of taking multi-step actions with limited human intervention. A Cloud Security Alliance survey on enterprise AI agents reported in April that 82% of surveyed organizations had unknown AI agents operating in their environments, while 65% reported an AI-agent-related incident during the previous 12 months. The research was commissioned by Token Security, so its sponsorship should be considered when interpreting the findings. For CISOs evaluating technologies such as Bedrock Data and OpenShell, the questions extend beyond whether a policy can technically block an action. Security teams will need evidence around latency, policy accuracy, false blocking, auditability and the effectiveness of controls when agents move between multiple tools and systems. Bedrock Data and NVIDIA have not publicly released independent production benchmarks for the combined integration. Developers and data-governance teams also have a stake. AI engineering teams could benefit from moving some enforcement outside individual agent frameworks rather than rebuilding equivalent controls for every AI application. For data-governance teams, the integration introduces another consideration: whether existing classifications and metadata are accurate enough to support runtime decisions. Bedrock Data says its Metadata Lake tracks information including what enterprise data is, where it resides, who can access it and how it is being used. That means policy decisions can potentially consider data context instead of relying solely on an agent's technical permissions. The effectiveness of that approach, however, depends on the quality and currency of the underlying metadata. Standards bodies are focusing on the same problem. The industry is also developing broader frameworks for autonomous-agent security. In February 2026, the U.S. National Institute of Standards and Technology launched its AI Agent Standards Initiative, focusing on secure and interoperable AI agents as autonomous systems gain greater access to external applications and enterprise information. That provides wider context for the Bedrock-NVIDIA development: runtime governance is emerging as a distinct security layer as enterprises move from AI assistants toward software capable of independently executing business tasks. Bedrock Data says Agent DLP for NVIDIA OpenShell is available now, including an observe-only mode that allows organizations to record policy decisions before switching on enforcement. For enterprise buyers, the next test will be how the technology performs in production environments, particularly across multiple AI frameworks, complex data estates and regulated workloads. Priyanshi Kharwade is a content writer specializing in B2B marketing and AI-driven revenue strategies. She approaches the GTM stack by treating every campaign as a study in behavioral science. Beyond that, she explores how internet culture and society intersect as the founder of Konsume. Currently studying communication, she tracks how media and technology shape human decision-making, bringing that exact perspective into everything she writes. say hi to Priyanshi

Bedrock Data has integrated its Agent DLP platform with NVIDIA OpenShell to provide data-aware policy enforcement for AI agents. The integration adds a policy evaluation layer where Bedrock Data assesses request payloads against enterprise data policies after OpenShell authorises them. NVIDIA OpenShell is an open source agent runtime that provides a secure, zero-trust environment for autonomous agents. Bedrock Data's technology addresses a key limitation: whilst permissions control which resources agents can access, they cannot distinguish between sensitive and harmless data within permitted operations. The platform evaluates agent actions based on data context, origin, combinations, and destination policies. OpenShell then enforces Bedrock Data's decisions at runtime, blocking actions when necessary. This helps prevent agents from inadvertently exposing sensitive data whilst completing tasks. The integration is available to Bedrock Data customers today.