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QpiAI Open-Sources Quantum SDK for 8- and 25-Qubit Computer Accessquantum-computing

QpiAI Open-Sources Quantum SDK for 8- and 25-Qubit Computer Access

QpiAI has released its Quantum SDK as open-source software, giving developers a pathway to run algorithms on the company’s 8-qubit and 25-qubit quantum computers via QpiAI-QCloud. The Python-based toolkit includes both local state-vector and density matrix simulators, allowing for algorithm prototyping and validation before utilizing actual quantum hardware. This move is designed to expand access to quantum software development for a global audience, from researchers and startups to enterprise innovation teams. “Quantum computing will scale only when developers can experiment, learn, and deploy without friction,” says Lakshya Priyadarshi, VP, Quantum Platforms & Solutions at QpiAI. QpiAI Quantum SDK Enables Algorithm Development and Hardware Access QpiAI has empowered developers with access to quantum computing resources through the open-source release of its Quantum SDK, providing a pathway to algorithm prototyping and direct hardware execution. The software, available at https://github.com/qpiai/quantum-sdk, represents a deliberate effort to democratize quantum software development, extending its reach beyond established research institutions to a global network of developers, startups, and enterprise innovation teams. QpiAI intends the SDK to serve as a foundation for building specialized quantum solutions across diverse fields including finance, logistics, materials science, and artificial intelligence. The Python-based SDK streamlines the development process with features designed for both novice and experienced quantum programmers. The SDK is engineered to support AI-assisted and agentic development workflows, enabling faster prototyping and implementation of quantum applications. QpiAI is actively targeting educational institutions, offering a ready-made foundation for quantum computing coursework, research projects, and developer training programs, with early adopters eligible for preferential commercial terms through the QpiAI Academic & Innovation

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QpiAI Open-Sources Quantum SDK for 8- and 25-Qubit Cloud Accessquantum-computing

QpiAI Open-Sources Quantum SDK for 8- and 25-Qubit Cloud Access

QpiAI has released its Quantum SDK as open-source software, immediately providing developers with a pathway to run algorithms on the company’s 8-qubit and 25-qubit quantum computers via QpiAI-QCloud. The Python-based toolkit includes both local state-vector and density matrix simulators, allowing for algorithm prototyping and validation before utilizing actual quantum hardware. This move is designed to expand access to quantum software development for a global audience, fostering innovation across industries like finance, logistics, and artificial intelligence. “Quantum computing will scale only when developers can experiment, learn, and deploy without friction,” said Lakshya Priyadarshi, VP, Quantum Platforms & Solutions, QpiAI, emphasizing the SDK’s role as a bridge between theory and real-world application. QpiAI Quantum SDK Enables Algorithm Development and Hardware Access QpiAI has empowered developers with direct access to quantum hardware through the open-sourcing of its Quantum SDK, a move that bypasses the typical limitations of simulation-only environments and facilitates real-world algorithm testing. The Python-based toolkit is now freely available at https://github.com/qpiai/quantum-sdk and allows users to deploy algorithms on QpiAI’s 8-qubit and 25-qubit quantum computers via the QpiAI-QCloud platform at https://qcloud.qpiai.tech, representing a significant step toward democratizing access to quantum resources. This release isn’t merely about providing software; it’s about establishing a tangible connection between theoretical development and practical execution, crucial for accelerating progress in the field. QpiAI intends this release to broaden participation in quantum software development, targeting developers, researchers, universities, startups, and enterprise innovation teams globally. This dual approach is designed to optimize the development lifecycle, allowing for rapid iteration and refinement of quantum solutions. The toolkit is engineer

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Alliance University, QpiAI establish quantum computing centre - Evertiqquantum-computing

Alliance University, QpiAI establish quantum computing centre - Evertiq

© Alliance Business | March 30, 2026 Alliance University, QpiAI establish quantum computing centre Evertiq The centre is expected to serve startups, multinational technology companies, academic researchers, and members of the defence and aerospace sectors located in and around Bengaluru. Alliance University, in partnership with QpiAI, has announced the establishment of a commercially accessible quantum computing experience centre at the university’s Electronic City campus in Bengaluru. The facility, called AU QUASAR (Quantum AI School of Advanced Research), will provide hands-on access to an 8-qubit superconducting quantum system, enabling users to work directly with quantum hardware, according to a press release.The centre is expected to serve startups, multinational technology companies, academic researchers, and members of the defence and aerospace sectors located in and around Bengaluru. At the core of the collaboration is QpiAI’s QVidya 8-qubit superconducting quantum system. The platform has been developed indigenously and is paired with the QpiAI Explorer software environment. “This partnership embodies our vision of making quantum computing accessible to every Indian innovator, researcher, and enterprise,” said Dr. Nagendra Nagaraja, Founder & CEO of QpiAI. “By combining QpiAI's indigenous and sovereign quantum technology with Alliance University's academic excellence and strategic location, we are creating a national reference site that will accelerate India's quantum computing adoption and contribute meaningfully to the National Quantum Mission goals.”“AU QUASAR is not merely a reference installation; it is designed as a living model of academic-industry collaboration in its truest sense. It will integrate degree programs, research, enterprise engagement, and Quantum Computing as a Service (QCaaS) under one roof,” said Abhay G Chebbi, Pro-Chancellor of Alliance University.

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QpiAI Achieves High Speed Quantum Error Correction on Superconducting Systems with New Decoder Platform - Business Wire Indiaquantum-computing

QpiAI Achieves High Speed Quantum Error Correction on Superconducting Systems with New Decoder Platform - Business Wire India

QpiAI Gen-1 25 qubit Quantum computer Indus, picture from QpiAI Bangalore centre with CEO Dr Nagendra Nagaraja (Left) and VP of Quantum hardware Dr Manjunath R V (Right). A scalable quantum error correction system has been developed by QpiAI to enable fast, scalable error correction using a rotated surface code architecture. The decoder, based on a union-find algorithm, is designed to operate in real time alongside superconducting qubits and represents a key step toward practical fault-tolerant quantum computing. A scalable quantum error correction system has been developed by QpiAI to enable fast, scalable error correction using a rotated surface code architecture. The decoder, based on a union-find algorithm, is designed to operate in real time alongside superconducting qubits and represents a key step toward practical fault-tolerant quantum computing. QpiAI, a leader in quantum computing and generative AI, announced its maiden external funding of $6.5 million to build Quantum computing and Generative AI products and platforms. QpiAI, a leader in quantum computing and AI today announced QpiAISense™ platform for room temperature qubit control. QpiAISense™ accelerates ML library using discrete FPGA DSPs currently. But in future it would support massive ML compute capability as much as 8000 trillion operations per second per watt (8000 Tops/watt ) using Qpisemi’s (https://www.qpisemi.tech) silicon photonics based AI20P001 to be integrated on QpiAISense™ platform. 5th Floor, 405-B DLF Cyber Park,Tower- B, Sector-20 Udyog Vihar Phase- lll Gurugram Haryana 122016 Copyright © 2026 Business Wire India. All Rights Reserved.

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QpiAI Achieves High-Speed Quantum Error Correction on Superconducting Systems with New Decoder Platform - HPCwirequantum-computing

QpiAI Achieves High-Speed Quantum Error Correction on Superconducting Systems with New Decoder Platform - HPCwire

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QpiAI Implements High-Speed Hardware Decoder for 64-Qubit Kaveri Processorquantum-computing

QpiAI Implements High-Speed Hardware Decoder for 64-Qubit Kaveri Processor

QpiAI Implements High-Speed Hardware Decoder for 64-Qubit Kaveri Processor QpiAI has reported the implementation of a high-performance quantum error correction (QEC) decoder platform for its 64-qubit Kaveri superconducting quantum processor. The system utilizes a distance-5 rotated surface code (d = 5) requiring 49 physical qubits to encode a single logical qubit. The decoder is based on a union-find algorithm executed on custom hardware rather than traditional CPU or GPU architectures. This design aims to provide a scalable framework for real-time error detection and correction, serving as a technical milestone within the framework of India’s National Quantum Mission (NQM). The custom hardware decoder achieves an end-to-end cycle latency of 1.5 microseconds, with the decoding operation itself completed in less than 1 microsecond (typically within 40 clock cycles). This represents a significant reduction in latency compared to existing software-based decoders, which often require approximately 60 microseconds for distance-5 codes. By maintaining a cycle time of 1.5 microseconds, the platform can perform five rounds of stabilizer measurements per cycle to detect both qubit and measurement errors while remaining well within the coherence window of the Kaveri hardware. The Kaveri QPU reports qubit coherence times of approximately 100 μs for T1 and 95 μs for T2, providing sufficient headroom for multiple consecutive error-correction cycles. The architecture is specifically optimized for surface-code-friendly qubit connectivity to facilitate efficient stabilizer measurements. Supported by investment from the Department of Science and Technology (DST), the development is intended to move India’s quantum infrastructure toward fault-tolerant utility. Future iterations of the roadmap include the support for distance-7 codes and the integration of quantum low-density parity-check (qLDPC) codes to further optimize physical-to-logical qubit ratios. For technical specifications

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QpiAI to Deploy 25-Qubit Superconducting Quantum System at IIIT-Dharwadquantum-computing

QpiAI to Deploy 25-Qubit Superconducting Quantum System at IIIT-Dharwad

QpiAI to Deploy 25-Qubit Superconducting Quantum System at IIIT-Dharwad QpiAI has been awarded a contract to install its QpiAI Indus 25-qubit quantum computing system at the IIIT-Dharwad Quantum and AI Computing Center of Excellence (QAIC). This installation, which will be jointly accessed by IIIT-Raichur, marks the second deployment of a QpiAI quantum system in the state of Karnataka. The initiative is a component of the Karnataka Quantum Roadmap, a strategic framework aimed at establishing a $20 billion quantum economy by 2035. The deployment is intended to provide infrastructure for academic research, curriculum development, and commercial experimentation within India’s indigenous technology ecosystem. The QpiAI Indus is a full-stack superconducting quantum computer utilizing transmon qubits housed in a closed-cycle cryostat at a base temperature of 10 mK. The system reports single-qubit gate fidelities of 99.7% and two-qubit gate fidelities of 96%, with coherence times characterized by T1​ ≈ 30μs and T2 ​≈ 25μs. It features a vertically integrated stack, including the QpiAISense™ control and readout electronics and the QpiAI Explorer software platform. The hardware is designed for hybrid quantum-classical workflows, integrating directly with classical High-Performance Computing (HPC) nodes equipped with Intel Xeon processors and NVIDIA GPUs. The QAIC at IIIT-Dharwad will utilize the system to support a range of educational and industrial workloads. For academia, the platform will facilitate hands-on student training and faculty-led research in quantum algorithms and error correction. For commercial users, the center will offer Quantum Computing as a Service (QCaaS), allowing enterprises to test and validate use cases in logistics, pharmaceutical discovery, and financial optimization. QpiAI will provide ongoing operational support to assist users in onboarding and transitioning applications from simulated environments to the physical 25-qubit hardware. This deplo

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QpiAI and Alliance University Establish AU QUASAR Experience Center in Bengaluruquantum-computing

QpiAI and Alliance University Establish AU QUASAR Experience Center in Bengaluru

QpiAI and Alliance University Establish AU QUASAR Experience Center in Bengaluru QpiAI and Alliance University have established the AU QUASAR (Quantum AI School for Advanced Research) Experience Center at the university’s Electronic City campus in Bengaluru. The facility integrates QpiAI’s QVidya 8-qubit superconducting quantum system with the QpiAI Explorer software platform, providing localized hardware access for quantum research and development. This center serves as a commercial reference site for superconducting quantum technology, targeting engagement from over 200 global technology companies and India’s aerospace and defense sectors. The initiative is designed to align with the technical objectives of India’s National Quantum Mission (NQM) by fostering indigenous quantum infrastructure and a sovereign talent pipeline. AU QUASAR will provide Quantum Computing as a Service (QCaaS) for commercial and strategic clients, allowing for the execution of quantum circuits on a physical 8-qubit processor rather than in purely simulated environments. This service model is intended to facilitate proof-of-concept (PoC) validations and the characterization of superconducting qubit performance in a hybrid quantum-classical context. Academic integration at the center includes undergraduate, postgraduate, and doctoral degree pathways focused on quantum computing and artificial intelligence. By combining physical system access with structured research programs, the facility aims to bridge the gap between theoretical study and industrial application. The center is expected to be operational in the coming months, providing a scalable model for future quantum technology hubs focused on education, research, and commercial engagement within India’s technology corridor. For technical details on the QVidya 8-qubit system and the AU QUASAR research pathways, consult the official QpiAI announcement here. March 25, 2026 Mohamed Abdel-Kareem2026-03-25T10:24:17-07:00 Leave A Comment Cance

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QpiAI Achieves High-Speed Quantum Error Correction on Superconducting Systems with New Decoder Platformquantum-computing

QpiAI Achieves High-Speed Quantum Error Correction on Superconducting Systems with New Decoder Platform

Insider Brief QpiAI has developed a hardware-based quantum error correction decoder that significantly reduces correction time on superconducting quantum systems. The platform cuts error correction latency from tens of microseconds to ~1.5 microseconds using a union-find algorithm on a 64-qubit Kaveri processor. This approach enables real-time, scalable error correction within qubit coherence limits, supporting progress toward fault-tolerant quantum computing. PRESS RELEASE — QpiAI, a leading developer of integrated AI and quantum solutions for enterprises, today announced a major advance in quantum error correction (QEC), unveiling a high-speed decoder hardware platform that dramatically reduces the time required to detect and correct errors in real time on superconducting quantum processors. In research conducted by the company on its 64-qubit Kaveri quantum superconducting processor, the compact decoder hardware, based on a union-find algorithm, reduced the time for error detection and correction from tens of microseconds using conventional software approaches to roughly 1.5 microseconds per correction cycle — addressing a critical barrier to achieving scalable, practical quantum computers. The system implements an industry-leading distance-5 rotated surface code using 49 physical qubits. Each decoder instance runs on a single QpiAI Kaveri QPU, allowing one decoder instance per chip. The architecture is optimized to support efficient decoding and integration with existing quantum hardware. “The performance of our new decoder platform demonstrates a practical pathway toward scalable, hardware-accelerated quantum error correction,” said QpiAI founder and CEO Nagendra Nagaraja, Ph.D. “Compatible with widely used superconducting transmon qubits, the platform limits the need for additional classical support from CPUs and GPUs. QpiAI is also developing next‑generation error‑correction methods tailored to our own fluxonium‑based qubits as well as architectures designed

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