There is a quiet, terrifying reality inside every enterprise trying to secure its data today. We are aggressively handing over the keys to the kingdom to AI agents — allowing them to query databases, read sensitive documents, and move information autonomously across the cloud. Yet, traditional data security was built for human beings operating in rigid, static environments. When an anomaly occurs or a compliance audit hits, security teams are left staring at fragmented logs, unable to trace whether a massive database query was run by a legitimate engineer, a compromised microservice, or a rogue autonomous agent.
It takes builders with a profound grasp of population-scale data security having literally designed the internal security systems at companies like Meta to look at this invisible chaos and solve it at the root. That is exactly what Apurv Garg, Krishna Bagadia, and Akash Mandal are doing with Aurva.
Founded in 2022, Apurv and the team are building the definitive runtime data security and observability platform for the AI and agentic era.
Aurva deploys an identity-aware control plane that provides zero-impact, real-time visibility into exactly how data is being accessed and by whom. Instead of relying on static permissions that inevitably drift, it captures the full chain behind every data interaction at runtime: identity, action, data touched, destination, and outcome. Whether a complex query is initiated by a human, an API, or a non-human AI agent, Aurva ties it back to a verifiable identity. It seamlessly integrates into modern data environments, mapping sensitive data end-to-end, flagging anomalies, and blocking inappropriate use in the exact moment it happens.
The true moat here is uncompromising runtime visibility paired with deterministic enforcement. Aurva doesn’t just generate more false-positive alerts for an already exhausted security team; it provides irrefutable evidence of who touched what, processing billions of access events daily with zero application latency impact. By completely abstracting away the paralyzing fear of data exposure, it allows engineering teams to deploy dynamic AI workloads safely. It shifts the paradigm from retroactive guesswork to real-time, identity-centric truth.
The market? CISOs, security engineers, and data compliance teams at high-scale enterprises, fintechs, and cloud-native organizations who desperately need to innovate with AI without risking catastrophic regulatory or security failures.
Seeing builders of this caliber head-down, quietly architecting the heavy-duty security infrastructure that the agentic era will fundamentally rely on, is profoundly inspiring. They are giving security teams their visibility and their confidence back.
Let’s celebrate the builders.
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