AI/ML
With key Digital Personal Data Protection Act requirements taking effect on May 13, 2027, Indian enterprises are preparing for new obligations around consent, personal data protection and breach reporting, with penalties for certain violations reaching up to ₹250 crore.
Privaclave AI is expanding its focus in India to address a critical part of that mandate, the company said: moving beyond cataloging personal data to protecting it persistently as it is accessed and used. Privaclave said it has expanded its India footprint with local engineering support since last year and continues to hire additional resources.
According to Privaclave, DPDP readiness cannot stop at knowing where sensitive data lives, since the real test begins when that data is accessed and used. As AI assistants, agents, APIs and applications increasingly interact with personal data, the company said, enterprises need protection that understands context and acts at runtime.
The company's Runtime Data Insights & Protection platform is designed to address that gap, according to Privaclave. The platform detects sensitive information in flight, evaluates identity, intent, business context and data sensitivity, and applies data-centric protection before exposure, the company said, and is designed to deploy without application rewrites, SDKs, client or agent installs, or extensions.
Sid Dutta, founder and CEO of Privaclave AI, said the shift in how AI systems interact with data requires a new security approach. "AI is fundamentally changing how sensitive data is accessed and shared," he said. "Discovery and governance are essential, but they do not prevent data exposure. Organizations must understand who or what is requesting the data, why it is being requested, and what should be exposed in that context. Intent is the new security perimeter. Context is king."
US fintech LXMQ, which is building an AI decision engine for the U.S. credit-card economy, selected Privaclave this August as a design partner to evaluate runtime protection before scaling to consumers, according to the company. Privaclave said LXMQ's engine continuously reasons over financial data, reflecting the increasingly dynamic, AI-driven architectures being built across Indian BFSI, healthcare and other industries. The company said its platform is designed to complement existing data security posture management, data loss prevention and identity and access management investments by adding runtime protection wherever sensitive data moves.
Privaclave AI is expanding its focus in India to address a critical part of that mandate, the company said: moving beyond cataloging personal data to protecting it persistently as it is accessed and used. Privaclave said it has expanded its India footprint with local engineering support since last year and continues to hire additional resources.
According to Privaclave, DPDP readiness cannot stop at knowing where sensitive data lives, since the real test begins when that data is accessed and used. As AI assistants, agents, APIs and applications increasingly interact with personal data, the company said, enterprises need protection that understands context and acts at runtime.
The company's Runtime Data Insights & Protection platform is designed to address that gap, according to Privaclave. The platform detects sensitive information in flight, evaluates identity, intent, business context and data sensitivity, and applies data-centric protection before exposure, the company said, and is designed to deploy without application rewrites, SDKs, client or agent installs, or extensions.
Sid Dutta, founder and CEO of Privaclave AI, said the shift in how AI systems interact with data requires a new security approach. "AI is fundamentally changing how sensitive data is accessed and shared," he said. "Discovery and governance are essential, but they do not prevent data exposure. Organizations must understand who or what is requesting the data, why it is being requested, and what should be exposed in that context. Intent is the new security perimeter. Context is king."
US fintech LXMQ, which is building an AI decision engine for the U.S. credit-card economy, selected Privaclave this August as a design partner to evaluate runtime protection before scaling to consumers, according to the company. Privaclave said LXMQ's engine continuously reasons over financial data, reflecting the increasingly dynamic, AI-driven architectures being built across Indian BFSI, healthcare and other industries. The company said its platform is designed to complement existing data security posture management, data loss prevention and identity and access management investments by adding runtime protection wherever sensitive data moves.
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