ArgusAI maps what each Google AI agent can access and enforces data access policies for AI systems, extending AI Risk Surface governance to agents built on Google Cloud
Bedrock Data, the platform provider for data-centric security, governance and management, announced that Bedrock Data ArgusAI now governs AI agents built on Google Vertex AI Search and Dialogflow. Conventional DSPM tools were built to locate sensitive data across enterprise environments, an approach designed before enterprises began deploying AI agents at scale. ArgusAI takes a different approach. With this new integration, ArgusAI maps the data connected to each Vertex AI Search and Dialogflow application, classifying it by sensitive data type and domain and enabling teams to write and enforce enterprise data access policies for AI systems.
By adding support for Google’s Vertex AI Search and Dialogflow frameworks, Bedrock Data enables enterprises to apply consistent governance standards to their AI portfolios regardless of which AI infrastructure powers those agents or where the data lives.
“Enterprises are accelerating AI adoption to stay competitive, and their proprietary data is their competitive advantage. Bedrock Data ArgusAI is built to facilitate scaling AI by enabling safe access to their most proprietary datasets so AI can produce business outcomes,” said Bruno Kurtic, CEO and co-founder of Bedrock Data. “Today we extend ArgusAI to Google Vertex AI, one of the leading AI platforms. ArgusAI now governs enterprise AI across Amazon Bedrock, Snowflake Cortex AI, ChatGPT Enterprise and Google Vertex AI.”
Governing the AI Risk Surface Across Cloud Providers
The ArgusAI for Google Vertex AI and Dialogflow integration extends Bedrock Data’s AI governance capabilities across AI provider ecosystems. By adding support for Google’s Vertex AI Search and Dialogflow frameworks, Bedrock Data enables enterprises to apply consistent governance standards to their AI portfolios regardless of which AI infrastructure powers those agents or where the data lives.
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Bedrock Data ArgusAI Maps and Governs the Google AI Agent Data Surface
Dialogflow CX and Dialogflow ES power conversational agents widely deployed in customer support scenarios, where public-facing accessibility makes them a target for attempts to extract sensitive information through conversational queries. Google Vertex AI Search enables organizations to build generative AI applications that retrieve data from internal data estate. ArgusAI now governs both, discovering the data connected to each framework, classifying it by sensitive data type and domain, and giving teams the guardrails needed to ensure agents access only what they are authorized to access by enterprise data access policies.
Building on Bedrock Data’s Metadata Lake, a continuously updated graph knowledge base that maps enterprise data across sensitivity, lineage, entitlements and business context, ArgusAI now extends that intelligence to AI agents built on Google Vertex AI framework.
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The new integration delivers three core capabilities:
- Data Bill of Materials (DBOM) for Google AI Agents: ArgusAI automatically discovers Vertex AI Search and Dialogflow applications and maps the data stores they access, currently including Google Cloud Storage buckets. It builds a continuously updated DBOM linking each agent to its underlying data, providing the foundation for AI governance.
- Sensitive Data and Domain Classification: ArgusAI classifies the data connected to each agent by specific sensitive data types, such as Social Security numbers, passport numbers and phone numbers, and by sensitive data domains, including HR data, financial data and security data. Security and governance teams gain the full context of what category of information an agent may surface in response to a query, not only which records it can reach.
- Natural Language Policy Guardrails: Teams can write policies governing AI agent data access in plain English, then let ArgusAI enforce. Policies such as “no Dialogflow agents should have access to any PII” or “only agent X should have access to SSNs and license numbers” translate into active controls, with alerts triggered when agent configurations or underlying data changes cause violations.
“Each AI platform defines data access in its own way. Vertex AI Search has data stores, Amazon Bedrock has knowledge bases and Snowflake Cortex has Cortex Search. Governing them separately means rebuilding policy logic for each one,” said Pranava Adduri, CTO and co-founder of Bedrock Data. “Instead, we represent every AI system and the data it touches in one graph inside the Metadata Lake. A policy written once applies consistently whether the agent runs on Google, AWS or Snowflake. Adding Vertex AI meant extending the graph connections. The governance model didn’t change.”
