MagiQware Secures €575K Pre-Seed to Optimize Quantum Error Correction

MagiQware has secured €575,000 in pre-seed funding led by Graduate Ventures, with participation from Delft Enterprises B.V., to address a core challenge hindering the advancement of practical quantum computers. The startup is focused on optimizing a critical component of quantum error correction, and early results demonstrate up to a 40% reduction in circuit length through a novel combination of reinforcement learning and quantum compiler optimization. This improvement is an important step towards scalable and cost-effective quantum computing, as reducing resource overhead becomes increasingly vital for commercial deployment. Graduate Ventures stated that MagiQware’s potential lies in its ability to “remove a fundamental bottleneck in fault-tolerant quantum computing” by applying advanced AI techniques. The new funding will accelerate the development of MagiQware’s technology and foster collaborations within the growing quantum computing industry. This focus allows MagiQware to position itself as a specialist software provider, offering performance improvements to full-stack quantum computing companies without requiring extensive in-house development of these complex optimization tools. The founding team, comprised of Arash Ahmadi, Shakeeb Majid, Sahar Hejazi, and Ali Moghaddam, brings a multidisciplinary skillset encompassing quantum computing, artificial intelligence, software engineering, and physics. Beyond the pre-seed round, MagiQware recently won the Holland HighTech SME Call, initiating a collaborative project with the University of Amsterdam to further develop AI-powered software for magic state factory optimization; this project aims to accelerate the commercialization of quantum computing and strengthen the Netherlands’ position in the emerging quantum technology sector. The new funding will support ongoing technology development and expand collaborations within the rapidly evolving quantum computing industry. These factories are responsible for generating the specialized quantum states necessary to detect and correct errors, and MagiQware’s approach focuses on optimizing their efficiency through artificial intelligence. The company’s core innovation lies in combining reinforcement learning with quantum compiler optimization, dynamically improving factory performance and reducing the substantial computational demands of fault-tolerant quantum computing. This reduction is particularly important as the field transitions from theoretical research toward practical applications, where resource overhead will become a defining factor in commercial viability. Early results have demonstrated up to a 40% reduction in circuit length , representing an important step towards scalable and cost-effective quantum computing. MagiQware Source: https://yesdelft.com/news/magiqware-secures-e575k-pre-seed-to-advance-quantum-computing/ Stay current. See today’s quantum computing news on Quantum Zeitgeist for the latest breakthroughs in qubits, hardware, algorithms, and industry deals. Tags: The Neuron With a keen intuition for emerging technologies, The Neuron brings over 5 years of deep expertise to the AI conversation. Coming from roots in software engineering, they've witnessed firsthand the transformation from traditional computing paradigms to today's ML-powered landscape. Their hands-on experience implementing neural networks and deep learning systems for Fortune 500 companies has provided unique insights that few tech writers possess. From developing recommendation engines that drive billions in revenue to optimizing computer vision systems for manufacturing giants, The Neuron doesn't just write about machine learning—they've shaped its real-world applications across industries. Having built real systems that are used across the globe by millions of users, that deep technological bases helps me write about the technologies of the future and current. Whether that is AI or Quantum Computing. Latest Posts by The Neuron: IQM Quantum Computers Acquires Quantistry July 6, 2026 University of California, Berkeley Finds ECG Biomarker July 6, 2026 Yonsei University Team Builds Continuous-Variable QNN for Wafer-Map Defect Classification July 6, 2026