SEMI AI, a new technology platform that integrates human judgment with machine intelligence, is set to soft launch on India's 77th Republic Day. Positioned as the world's first half-machine, half-human AI system, SEMI AI promises to deliver more accurate, ethical, and context-aware decision-making across multiple sectors.
SEMI AI functions as an intelligent routing system that assesses incoming queries to decide what can be handled by AI and what requires human judgment. Its machine learning algorithms analyse data, identify patterns, and deliver instant responses for routine tasks, while more complex issues involving judgment, ethics, or cultural context are escalated to qualified human experts within the SEMI AI network.
Saurabh Bhambri, Founder and CEO of SEMI AI, said: "SEMI AI is Made in India, by Indians, and for Indians. This launch on Republic Day symbolizes our commitment to building technology that serves the nation and reflects Indian values. We are proud to dedicate this platform to the people of India on this historic day."
Bijay Singh Rajput, Co-founder and Chief Technology Officer of SEMI AI, said: "SEMI AI will make life easier for Indian citizens by supporting smarter decisions across industries. We also hope the Indian government will support this initiative so it can scale globally and make our country proud on the world stage."
This hybrid approach creates a continuous feedback loop, where human inputs help improve and refine the AI, while the technology ensures speed and scalability. By combining both, the platform addresses a key limitation of purely algorithm-driven systems, which often lack the contextual understanding and ethical depth needed for complex decision-making in India’s diverse environments.
The platform has potential applications spanning healthcare, governance, finance, education, and public services. In healthcare, it provides diagnostic support with doctor oversight. In finance, it offers risk assessment with human validation. In education, it enables personalized learning with teacher guidance. In public services, it resolves citizen queries with human escalation for complex cases.
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