Pioneering the Next Generation of Intelligent Systems
Query Machines develops quantum-enhanced deep learning architectures that leverage quantum computing principles including superposition, entanglement, and quantum search algorithms to overcome fundamental limitations in classical AI reasoning capabilities.
Current large language models are approaching a performance plateau. Despite exponential increases in compute and parameters, improvements on complex reasoning tasks have significantly slowed. Classical scaling strategies demonstrate diminishing returns on reasoning-intensive benchmarks.
Query Machines is pioneering a fundamentally different approach by integrating quantum computing principles directly into transformer architectures. Our quantum-enhanced attention mechanisms excel where classical approaches struggle: maintaining coherence across long-range dependencies, executing multi-step logical reasoning, and efficiently exploring complex solutions.
Our proof-of-concept demonstrations have validated measurable performance advantages, outperforming classical baselines with identical parameter counts on reasoning-intensive tasks including text classification with long-range dependencies and multi-step variable tracing.
Based in Delft, Netherlands—a global center for quantum computing research and innovation—Query Machines operates at the intersection of quantum physics and artificial intelligence, building the foundation for the next generation of reasoning systems.
Query Machines operates three parallel research directions, each targeting distinct aspects of quantum-enhanced reasoning architectures
Replacing classical attention mechanisms with quantum multi-head attention layers that leverage quantum superposition to explore attention patterns simultaneously and entanglement to preserve long-range semantic dependencies.
Primary Applications: Code generation, document understanding, scientific reasoning
Next-generation architecture featuring dynamic quantum resource allocation based on input complexity, optimizing the efficiency-performance trade-off for production deployment scenarios.
Core Innovation: Context-aware computational resource scaling
Integration of Grover's quantum search algorithm into recursive reasoning architectures (HRM/TRM) to achieve quadratic speedup in solution space exploration during multi-step inference.
Target Applications: Formal verification, abstract reasoning, constraint satisfaction
Deep expertise at the intersection of quantum computing and machine learning
Co-Founder & Chief Executive Officer
MSc in Applied Physics for Quantum Devices & Quantum Computing from TU Delft. Background in private equity, consulting, and AI agent development. Leading Query Machines' research strategy and business operations, bridging quantum physics principles with practical AI applications.
Co-Founder & Chief Technology Officer
MSc in Applied Physics for Quantum Devices & Quantum Computing from TU Delft. Leading the development and implementation of quantum-enhanced architectures, translating quantum algorithms into practical AI systems.
Interested in research collaboration, strategic partnership, or learning more about our quantum AI technology?
We welcome discussions with academic institutions, enterprise partners, investment firms, and technical advisors.
Delft, Netherlands
querymachines.com