U.S. Data Privacy Framework: Velotix Advocates Dynamic Governance
Velotix urges Congress to build U.S. data privacy law on dynamic, machine-enforceable policy, not static rules, for better speed & protection.
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Velotix CEO Dr. Adi Hod urges Congress to build U.S. data privacy law on real-time, machine-enforceable policy not static, state-by-state rules.
NY, UNITED STATES, September 8, 2026 /EINPresswire.com/ — In response to the House Committee on Energy and Commerce’s Request for Information, Velotix CEO Dr. Adi Hod calls for machine-interpretable, real-time enforceable privacy policy as the foundation of any national privacy standard
Velotix, the AI-powered data security and access platform trusted by enterprises to govern sensitive data at scale, today announced its response to the U.S. House Committee on Energy and Commerce’s Request for Information (RFI) on establishing a comprehensive federal data privacy and security framework.
In its submission, Velotix argues that the debate over privacy legislation has focused too narrowly on the fragmentation of state-by-state rules — and has overlooked a deeper structural problem: the mismatch between static, text-based governance policies and the dynamic, constantly evolving data environments that modern enterprises actually operate.
“State-level fragmentation is a real challenge, but it isn’t the whole story,” said Dr. Adi Hod, Co-Founder and CEO of Velotix. “The bigger issue is that privacy policy is still written as if data environments hold still. They don’t. Infrastructure changes, employees change roles, regulations change, and AI is introducing entirely new categories of sensitive data. A federal framework that doesn’t account for that constant motion will be outdated the moment it’s signed.”
A Call for “Actionable” Policy
Velotix’s response outlines a policy approach built on three principles it believes any durable federal framework should reflect:
Machine-interpretable policy — privacy rules written so they can be automatically translated into technical controls across an organization’s systems, rather than manually reinterpreted platform by platform.
Real-time, continuous enforcement — moving beyond point-in-time audits toward systems that adapt access and protection automatically as data, roles, and regulations shift — including during employee onboarding, role changes, and departures.
End-to-end traceability — a clear, demonstrable line from written policy to actual system-level permissions, so organizations can show regulators exactly how a privacy rule is enforced in practice.
The response also addresses artificial intelligence’s dual role in privacy: AI as a tool that helps organizations classify, monitor, and protect data at a scale no human team could manage, and AI as a technology that itself requires new privacy safeguards — including access limits, model transparency, and auditing of how AI systems use sensitive training data.
“AI and privacy protection shouldn’t be treated as competing priorities,” Dr. Hod added. “When they’re designed to work together, organizations get both stronger protection and faster, safer access to the data they need to compete.”
Why It Matters for U.S. Businesses
Velotix contends that the current patchwork of static, manually enforced privacy controls creates real business costs: security gaps from inconsistent enforcement, innovation bottlenecks caused by compliance uncertainty, reduced data utility as organizations default to overly restrictive access policies, and rising compliance costs from maintaining multiple parallel privacy programs.
By contrast, the company argues that a federal standard built on actionable, dynamically enforced policy would let U.S. businesses move faster with their data while strengthening, not weakening, privacy protections for consumers.
“Speed and protection aren’t opposing goals,” said Dr. Hod. “Done right, they reinforce each other. A federal framework that recognizes this can help American businesses lead in the global economy while setting a new standard for privacy in the digital age.”
Velotix is an AI-powered data security and access platform that helps enterprises discover, govern, and share sensitive data without compromising compliance. Using policy-based access control (PBAC) and AI-driven automation, Velotix reduces data access times from months to minutes, continuously enforces policy across cloud, on-premises, and hybrid environments, and gives organizations real-time visibility into how data is accessed and protected.
Velotix is recognized as a Selected Vendor in the Gartner Guide for Data Security Platforms and is ISO 27001 certified. The company serves enterprises across financial services, healthcare, life sciences, telecommunications, and other data-intensive industries.
For more information, visit www.velotix.ai.
About Dr. Adi Hod
Dr. Adi Hod is Co-Founder and CEO of Velotix. His work focuses on enterprise data access, dynamic data governance, AI-driven privacy and security, and policy-based approaches designed to make data more usable while maintaining appropriate controls.
Imran qureshi
Velotix
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