Bengaluru-based QpiAI envisions a roadmap spanning 1,000 qubits and is building what it calls the worlds first commercially viable quantum-AI stack.
Aug. 01, 2025 –
Quantum computing is not just about speeding things up; it is about solving problems that today’s computers cannot touch. From new materials and drug discovery to encryption and advanced manufacturing, its potential runs deep, but making it useful means building more than just a quantum chip. You need the whole stack: cryo-hardware, control electronics, software, error correction, and AI to manage and run it all.
Bangalore-based QpiAI is developing a vertically integrated, AI-powered, full-stack quantum computing platform designed to run inside data centers. The company is building the entire control electronics, system software, compilers, and AI workflows in-house. It recently closed a $32 million (USD) Series A funding round led by Avataar Ventures and India’s Department of Science and Technology under the National Quantum Mission, with participation from both existing and new investors.
Founded by Dr Nagendra Nagaraju, an engineer with a background in chip design at NVIDIA and research in AI and wireless systems, QpiAI started as a natural extension of both academic passion and industry insight.
“I had been interested in quantum physics since Class 12, back in the 1990s,” said Nagaraju. “Nature is quantum by default. This includes quantum chemistry, quantum mechanics, photosynthesis, and even how plants absorb fertilizer. However, most of our AI today is trained on digitized human-generated data. To make AI more powerful, we needed to interact with nature in its own language, and that was quantum.”
The company’s long-term goal is to combine bits, qubits, and neurons to build intelligence modelling systems that are more efficient and far more powerful than today’s data-heavy AI infrastructure.
QpiAI has already developed a 25-qubit superconducting quantum processor. Its roadmap leads to 1000 qubits, with intermediate systems named Kaveri (64 qubits), Yamuna (128), Ganges (256), and Everest (1000). These are noisy intermediate-scale quantum (NISQ) systems.