Matters.AI and Upwind announced a native API integration on October 5, 2026, connecting cloud exposures with sensitive data risks. The integration targets security teams that need clearer context before prioritizing cloud vulnerabilities for remediation.
The partnership combines Upwind’s cloud security visibility with Matters.AI’s data classification and Database Activity Monitoring capabilities. It links workloads, identities and network paths to sensitive data, access details and activity across affected datastores.
A major cloud alert can show serious exposure without identifying the business records sitting behind it. The combined platform adds data context, helping security teams separate technical severity from actual business risk.
Upwind contributes runtime information covering workloads, processes, identities, network paths and real-time cloud execution. Matters.AI then adds data discovery, classification, access information and query-level activity from Database Activity Monitoring.
The integration maps Upwind findings to the relevant datastore inside Matters.AI and enriches those findings. Security teams can then review exposures through a queue that combines cloud context with data sensitivity.
Matters.AI uses a 24-hour ingestion cycle for posture and configuration findings received through the integration. When Upwind serves as the authoritative posture source, Matters.AI suppresses duplicate posture findings.
The setup also eliminates the need for another posture scanner for cloud accounts already connected to Upwind. Customers connect existing Upwind organizations through the native API connector, while operational metadata moves between platforms.
Harsh Sahu, co-founder and CTO at Matters.AI, called the integration a major step for data security. He said runtime visibility can connect live cloud execution with the sensitive assets requiring protection.
Alon Saban, head of tech alliances at Upwind Security, highlighted the value of combining runtime intelligence with data context. He said the partnership can help customers build a clearer risk picture and prioritize critical exposures.
The integration also strengthens investigation and compliance workflows by connecting infrastructure findings with data activity evidence. The approach shifts cloud security toward prioritizing exposures based on what sensitive information they can actually affect.
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