ParadigmIT launches ‘Sovereign AI in a Box’ for secure, on-premise govt deployments

/ 2 min read
Summary

Unlike conventional AI systems that depend on constant internet connectivity and cloud-based processing, Sovereign AI in a Box is fully on-premise. 

Andhra Pradesh Chief Minister N. Chandrababu Naidu with Sridhar Gadhi (second from left), Founder and Executive Chairman, Quantela Inc, at the India AI Impact Summit 2026, in New Delhi.
Andhra Pradesh Chief Minister N. Chandrababu Naidu with Sridhar Gadhi (second from left), Founder and Executive Chairman, Quantela Inc, at the India AI Impact Summit 2026, in New Delhi.

ParadigmIT, led by Founder and Chairman Sridhar Gadhi, has launched Sovereign AI in a Box, positioning it as India’s first production-ready AI platform designed specifically for government departments, utilities, defence establishments, police agencies and public service organisations that require complete data control within their own premises. 

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With over 20 years of experience deploying critical digital infrastructure across more than 100 Indian cities and institutions, ParadigmIT said the platform addresses a key concern for public institutions: using advanced AI capabilities without relying on cloud services or moving sensitive data outside controlled environments. 

Unlike conventional AI systems that depend on constant internet connectivity and cloud-based processing, Sovereign AI in a Box is fully on-premise. The platform enables institutions to operate AI models within secure infrastructure, ensuring jurisdictional control, data privacy and operational continuity. 

On Friday, Andhra Pradesh Chief Minister N. Chandrababu Naidu in his X handle wrote, "Had a productive meeting with Mr. Sridhar Gadhi, Founder & Executive Chairman at Quantela Inc, at the India AI Impact Summit 2026 in New Delhi today. We discussed leveraging AI-driven solutions to accelerate smart governance and citizen-centric innovation."

What sets it apart 

Sovereign AI in a Box is designed as a fully integrated solution rather than a standalone hardware or software offering. It includes specialised equipment, pre-trained AI models tailored to government use cases and ready-to-deploy applications for tasks such as infrastructure monitoring, policing support, citizen service enhancement, energy management, and command centre decision-making. 

The platform can function in completely disconnected environments or regions with limited connectivity. It comes with over 125 AI tools built specifically for public-sector operations and can scale from a single district office to a nationwide deployment. The system is designed to integrate with existing government infrastructure without disrupting ongoing operations. 

Built with India’s operational diversity in mind, the platform supports multiple languages, is cost-efficient and can operate across varied geographical conditions. By delivering AI capabilities directly to districts and command centres, it reduces the need for heavy cloud infrastructure investments. 

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A sift in government AI strategy 

Gadhi said the first phase of global AI development centred on large cloud-based models, but governance requires a different approach. 

“Governments operate mission-critical systems — policing, land records, utilities, public health — where accuracy, accountability and jurisdictional control are essential,” he said. “The future of AI in governance is domain-specific intelligence operating within secure infrastructure.” 

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According to ParadigmIT, the platform represents a shift from traditional technology procurement to outcome-driven deployments, where institutions adopt ready-configured intelligence systems aligned with their operational needs. 

ParadigmIT designs and operates large-scale digital infrastructure across Smart City command centres, public health systems, land digitisation and cybersecurity platforms. The company also founded the TechBharat Foundation, a non-profit AI centre focused on AI for public good. 

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With this launch, the firm aims to enable secure, locally governed AI systems that deliver measurable outcomes while maintaining institutional control over data and decision-making frameworks. 

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