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Bedrock Data has introduced native support for Atlassian Confluence within its modern Data Security Posture Management (DSPM) platform. This integration provides security teams with visibility into sensitive data stored in Confluence, maps how that data flows into AI systems, and reveals potential exposure risks during AI model inference, addressing growing concerns as unstructured SaaS content increasingly serves as input for AI workflows.
As organizations adopt more SaaS platforms alongside AI technologies, sensitive information such as trade secrets, intellectual property, and customer data increasingly resides in collaboration environments like Confluence. When this unstructured content feeds AI systems, including RAG implementations with services like AWS Bedrock Knowledge Bases, traditional security approaches fall short in tracking what data models can access and potentially expose in responses.
Bedrock Data’s approach stands out by connecting SaaS discovery, sensitive data classification, and AI inference lineage within a single DSPM platform. Beyond locating sensitive data, the integration traces how it reaches AI models, enabling teams to evaluate what information could surface during queries and whether unauthorized users might gain exposure. This provides actionable context for governance, compliance, and risk mitigation.
The solution delivers automated discovery of all Confluence spaces and content types, including folders, pages, live pages, and blogs. It performs detailed permission analysis to uncover effective access rights, even when obscured by inherited or indirect paths. AI-powered scanning classifies unstructured text for sensitive elements, indexing metadata in the Bedrock Metadata Lake. Security teams gain unified querying across diverse data sources, supporting faster risk identification without requiring write access.
“Confluence is one of the most requested SaaS data sources because, for many organizations, it holds vast amounts of internal knowledge, including trade secrets, intellectual property and customer information,” said Bruno Kurtic, co-founder, President, and CEO of Bedrock Data. “This content is increasingly used across analytics, collaboration and AI use cases including as a basis for RAGs. Organizations need to ensure it is properly classified, protected and compliant with internal governance standards and regulatory requirements, with clear visibility into how sensitive information is accessed and used.”
With this release, Bedrock Data extends DSPM coverage into the SaaS and AI ecosystems where enterprise data risk is rapidly shifting, helping organizations maintain visibility and control before exposures occur.
The Confluence integration is available immediately for Bedrock Data customers.
About Bedrock Data
Bedrock Data delivers continuous, context-driven security and governance for enterprise data across private cloud, IaaS, PaaS, SaaS and AI environments. Powered by its patented Metadata Lake and Serverless Outpost architecture, Bedrock Data autonomously discovers, classifies and contextualizes data in place without moving it outside customer boundaries. Its open, API-first design integrates with existing platforms and enables natural-language policy enforcement, AI governance and automated remediation at enterprise scale.
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