On October 5, 2026, Matters.AI and Upwind rolled out a native API integration designed to connect cloud exposures directly with sensitive data risks. This joint effort is aimed at security professionals seeking sharper context before they decide which cloud vulnerabilities to fix first.
By merging Upwind’s cloud security visibility with Matters.AI’s Database Activity Monitoring and data classification tools, the partnership ties workloads, identities, and network paths directly to sensitive data, access specifics, and datastore activity.
A critical cloud alert often highlights a severe exposure without revealing the actual business records at stake. By injecting data context into the mix, the integrated platform assists security teams in distinguishing between pure technical severity and genuine business risk.
Upwind brings runtime insights to the table—including details on workloads, processes, identities, network paths, and real-time cloud execution. Matters.AI complements this by providing data discovery, classification, access intelligence, and query-level activity derived from Database Activity Monitoring.
The integration correlates Upwind’s discoveries with the appropriate datastore inside Matters.AI, enhancing those alerts in the process. Consequently, security teams can evaluate vulnerabilities via a unified queue that blends cloud context with data sensitivity levels.
For posture and configuration findings pulled through the integration, Matters.AI relies on a 24-hour ingestion cycle. Furthermore, when Upwind acts as the primary posture source, Matters.AI automatically suppresses redundant posture findings.
Clients who already link their cloud accounts to Upwind can bypass the need for an additional posture scanner. Users simply connect their current Upwind organizations using the native API connector as operational metadata flows seamlessly between the two systems.
According to Matters.AI co-founder and CTO Harsh Sahu, the integration marks a significant milestone for data security, noting that runtime visibility bridges live cloud execution with the sensitive assets that need safeguarding.
Alon Saban, head of tech alliances at Upwind Security, emphasized the benefits of uniting runtime intelligence with data context, stating that the collaboration enables clients to construct a sharper risk profile and focus on high-priority exposures.
Furthermore, the integration bolsters compliance and investigation workflows by linking infrastructure findings directly to evidence of data activity. Ultimately, this methodology steers cloud security toward prioritizing vulnerabilities based on the actual sensitive information they might impact.
Also Read: QRKY.ai Integrates Scannable QR Designs into Brand Media Advertising
