Every person carries something that no technology company has ever been able to replicate on their behalf: a mind that belongs entirely to them. Thoughts form privately. Plans take shape internally. Decisions are weighed and made without anyone else watching. Nothing leaves that space until the person chooses to share it, through speech, gesture or writing.
Akhil Pamarthy believes artificial intelligence should work the same way. It is a view he admits runs against the current of the industry, and it shapes how he thinks about the future of technology for the organizations that matter most.
“Technology and AI should perform inference and operations, and support decision making in real time without any vulnerabilities,” Pamarthy says. “It should be as reliable as an individual entity, completely disconnected from the outside world, sovereign, safe and highly performing in nature.”
An Industry Built on Borrowed Intelligence
The prevailing model of AI today runs on connection. Organizations send their questions, documents and data across a network to systems operated by large technology providers. The intelligence lives somewhere else, on someone else’s servers, governed by someone else’s policies. Access is rented, and the arrangement only works as long as the connection holds.
For many industries, that trade has been worth it. Software companies, research teams, automation firms and service businesses have moved quickly to adopt AI and are already seeing the benefits.
But Pamarthy points to a gap that receives far less attention. The institutions with the most at stake are often the ones moving slowest, not because they lack interest, but because of privacy concerns and performance limits.
“The most critical work and decision making rarely happens in a typical office,” he says. “It often unfolds in legal houses, operating rooms, secure facilities, industrial sites, isolated areas and contested environments, where technology should operate autonomously and there may be no network at all.”
In those settings, a dependence on outside systems is not a minor inconvenience. It can mean exposed client files, compromised patient records, interrupted operations or a system that simply stops working when the signal drops.
The Human Brain as the Model
Pamarthy’s alternative begins with a simple comparison. Every person is equipped with a brain that works privately, for that person alone. All planning and decision making happens inside the body. No one else knows what a person is thinking until that person decides to disclose it.
“In the same way as a human brain, every institution and organization should have a digital brain,” he says, “and systems to harness their own intelligence on their own hardware infrastructure, without relying on big tech companies or service providers or network moderators for the sake of AI.”
That digital brain, in his view, should be able to live wherever an organization operates: on desktops and servers in an office, on edge devices in the field, on rugged hardware built for harsh conditions, and inside IoT systems and robotics. Wherever the work happens, the intelligence should be present, private and fully under the organization’s control.
The distinction he draws is one of ownership. Today, most organizations access intelligence that belongs to someone else. Pamarthy argues they should own their intelligence outright, on their own infrastructure, inside their own environments.
Why Privacy and Performance Go Together
Discussions about private AI often frame privacy as a cost, something an organization gains only by giving up speed or capability. Pamarthy sees it differently. In his view, intelligence that runs locally is not only more private but often more dependable.
A system that does not need to reach an outside server cannot be cut off by a network failure. It does not wait on a remote queue. It continues working in a basement records room, a hospital operating theater, an industrial plant or a remote location with no connectivity at all. For organizations where a delay or an outage carries real consequences, that reliability matters as much as confidentiality.
That is why Pamarthy refers to privacy and performance together. He believes organizations demanding both should not be asked to settle for one.
A Global Shift Already Underway
Pamarthy’s position may be unpopular inside parts of the technology industry, but the regulatory world is moving in a similar direction. According to the International Association of Privacy Professionals, 144 countries now enforce data protection and privacy laws, spanning sectors including healthcare, finance, defense and law. In the United States, 24 states now enforce comprehensive data privacy laws, layered on top of federal rules such as HIPAA and the Gramm-Leach-Bliley Act.
Analysts see the same trend in how organizations plan their infrastructure. Gartner projects that 75 percent of enterprises in Europe and the Middle East will move workloads to sovereign, local infrastructure by 2030.
To Pamarthy, these numbers describe a world in which regulated industries are being forced into an uncomfortable position: adopt AI and accept the risk, or avoid it and fall behind. He believes the choice itself is the problem.
Technology That Extends People
Underneath his position is a broader belief about what technology is for. Pamarthy holds that technology and AI should extend human capabilities effortlessly and meaningfully, not create new dependencies or new points of failure.
His personal path reflects that belief. Raised in Hyderabad, India, Pamarthy trained as a mechanical engineer before earning a master’s degree in computer and information sciences. Today, he is the founder of Offline Intelligence, where he focuses on building intelligence that runs on an organization’s own hardware. He describes himself as a software systems architect and lifelong technology enthusiast whose interest began somewhere familiar to many engineers.
“Video games got me into software,” he says, “and software got me into AI and robotics.”
That combination of mechanical and software thinking shapes how he sees intelligence: not as a remote service, but as something that should be built into the machine and the institution itself, the way a mind is built into a person.
A Vision Bigger Than Any Single Industry
Pamarthy’s goal is not limited to one sector. He wants to build efficient systems and AI for all of humanity, with particular attention to the organizations and institutions that demand privacy and performance most. These include legal teams, healthcare providers, financial institutions, critical infrastructure operators and national security organizations.
He sums up the mission in a single line: to empower humanity to flourish and operate without relying on a network for intelligence.
It is an ambitious idea, and he knows it challenges the direction much of the AI industry has taken. But for Pamarthy, the logic is simple. People already trust the most important decisions of their lives to a private, self-contained intelligence. He believes the institutions that protect human life and liberty deserve the same.
