Matters.AI, a Data Detection and Response (DDR) platform, has developed a native API integration with cloud and AI security company Upwind to help security teams assess which cloud exposures could affect sensitive business data. The integration combines Upwind’s security context with Matters.AI’s data discovery, classification and Database Activity Monitoring capabilities, reducing the need for teams to manually correlate findings across separate systems.
A high-severity cloud alert alone does not indicate which business records may be at risk. Upwind provides context on running workloads, processes, identities and network paths, while Matters.AI adds information about the data associated with those environments, including its sensitivity, access permissions and activity. Bringing these perspectives together enables security teams to investigate the relationship between an infrastructure exposure and the data it could potentially affect.
The integration maps Upwind findings to Matters.AI’s classification results for the affected datastore. For posture and configuration findings, Matters.AI uses a 24-hour ingestion cycle. Where Upwind is the authoritative posture source for an account, Matters.AI suppresses its own posture results to reduce duplication. Security teams can then use the resulting exposure queue to prioritise findings based on both cloud context and the sensitivity of the associated records. Database Activity Monitoring provides additional query-level information to support investigation and response.
According to Harsh Sahu, Co-Founder & CTO at Matters.AI, integrating Matters.AI with Upwind’s runtime visibility represents a significant step forward for data security. He said that enriching the company’s AI-native semantic engine with live process and socket telemetry gives security teams a comprehensive, single-pane view of data risk, linking real-time cloud execution directly to the sensitive assets being protected.
Alon Saban, Head of Tech Alliances at Upwind Security, said that Upwind provides real-time runtime data enriched with deep cloud security and AI security context, which Matters.AI can leverage to broaden and enrich its datasets. By connecting activity taking place in the cloud with the sensitive data at risk, he added, the integration gives customers a more complete picture of risk and helps them prioritise the issues that matter most.
Customers can connect their existing Upwind organisation through the native API connector. Matters.AI uses the cloud posture information already collected by Upwind, avoiding the need to onboard the same cloud accounts to a second posture scanner. Matters.AI’s scanning and classification take place within the customer’s environment, while operational metadata is exchanged through API connections.
The integration is designed to bring infrastructure findings, data classification and access activity together as a unified evidence base for security and compliance teams, helping organisations investigate exposures more efficiently and focus on risks involving their most sensitive data.