As enterprises rapidly adopt AI and cloud infrastructure, their sensitive data has scattered across SaaS apps, vector databases, endpoints, and chat logs. To protect it, security teams are forced to stitch together a fragmented mess of legacy tools — one dashboard for Data Loss Prevention (DLP), another for Data Security Posture Management (DSPM), and a third for insider risk. When a massive data incident occurs, these disconnected tools flood the SOC with thousands of meaningless alerts based on rigid pattern matches. Teams are left agonizingly trying to piece together the context manually, usually long after a breach has already happened. We are generating more security telemetry than ever, but we have completely lost the actual narrative.
It takes builders with a profound grasp of enterprise data architecture and the engineering rigor to solve this at the root. That is exactly what Keshava Murthy and Harsh Sahu are doing with Matters.AI.
Founded in 2022, Keshava and Harsh are building a deeply intelligent, AI-native data security platform that effectively acts as an autonomous AI Security Engineer for the enterprise.
Matters.AI unifies DSPM, real-time data detection and response, and insider risk management into a single, continuous intelligence layer. The platform continuously discovers and classifies sensitive data across cloud environments, endpoints, and SaaS applications like Google Workspace and Slack. Instead of just identifying that a credit card number exists in a file, it builds a live, dynamic data lineage graph — tracking exactly how data originates, transforms, and propagates across the organization. By modeling human intent and behavioral context, it understands the difference between a legitimate engineering workflow and a malicious data exfiltration attempt.
The true moat here is uncompromising context paired with automated governance. Matters.AI completely abstracts away the soul-crushing alert fatigue that burns out security analysts. When an incident unfolds, it doesn’t just ping a Slack channel; it instantly generates a structured, regulator-ready “Evidence Pack” detailing the exact identities, data flow, and response actions taken. It shifts the paradigm from retroactive, point-in-time audits to continuous, intelligent data protection that actually understands the business.
The market? CISOs, security leaders, and fast-growing global enterprises who desperately need to secure their sprawling data estates without slowing down their engineering teams or breaking legitimate workflows.
Seeing homegrown founders head-down, quietly architecting the intelligence layer that brings clarity and true context back to enterprise data security, is profoundly inspiring. They are giving security teams their visibility and their sleep back.
Let’s celebrate the builders.
w/ Jay Ingle
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