QAI is building a next-generation hybrid quantum–AI infrastructure that integrates quantum computing, AI supercomputing, and orchestration into a unified, production-ready platform.
The platform is designed to support real-world experimentation, scalable deployment, and long-term operation across hybrid workloads.
TECHNOLOGY & PLATFORM OVERVIEW
QAI's Technology & Platform layer integrates quantum computing, high-performance GPU infrastructure, and classical compute into a single coordinated environment. Through centralized orchestration, users can execute quantum algorithms, hybrid quantum–AI workflows, and large-scale simulations without managing infrastructure complexity.
QAI's platform is designed as a vertically integrated system that brings quantum computing, AI supercomputing, orchestration software, and dedicated infrastructure into a single, coherent architecture.
A DGX-accelerated environment for developing and validating quantum and hybrid quantum–classical algorithms at scale.
A hybrid QPU–GPU framework for exploring quantum-enhanced machine learning models and integrated training workflows.
A unified development layer based on NVIDIA CUDA-Q, enabling hybrid quantum–AI applications across QPU, GPU, and CPU resources.
A centralized orchestration layer coordinating workload execution, scheduling, and optimization across the entire platform.
QAI operates a full-stack hybrid architecture integrating quantum hardware, AI supercomputing infrastructure, orchestration software, and application layers into a single operational system. This enables coordinated execution across QPU, GPU, and CPU resources under unified control.
Superconducting quantum systems, DGX SuperPOD GPU clusters, and classical CPU compute nodes form the physical foundation of the platform.
Hybrid programming frameworks, quantum control systems, and simulation engines enable coordinated execution across quantum and classical environments.
Centralized orchestration, workflow automation, and resource scheduling unify quantum, AI, and HPC workloads into a single operational platform.
Domain-specific applications and APIs support advanced research and enterprise use cases across science, industry, and engineering.
QAI's hybrid quantum–AI platform is supported by a multidisciplinary engineering organization across quantum systems, AI/HPC infrastructure, data center engineering, and platform orchestration.
Engineering expertise supporting large-scale AI, HPC, and hybrid quantum workloads.
Integrated facility and systems engineering for high-density compute and quantum infrastructure.
Specialized engineering supporting quantum system deployment and hybrid execution.
Advisory capabilities supporting long-term quantum–AI adoption and ecosystem development.
These integrated compute zones form a unified foundation for executing hybrid quantum–AI workloads within a single facility, with reliability and control built directly into the physical infrastructure.
QAI's hybrid quantum–AI platform is governed by a centralized control and orchestration layer that coordinates quantum, AI, and classical resources for reliable execution, efficient scheduling, and sustained performance across hybrid workloads.
Centralized orchestration of hybrid quantum–AI workloads across QPU, GPU, and CPU resources, enabling coordinated execution of simulation, training, and optimization pipelines.
Dynamic allocation and optimization of compute, memory, network, and storage resources based on workload characteristics and system availability.
Real-time visibility into system health, workload execution, and performance metrics across quantum systems, DGX SuperPOD clusters, and facility infrastructure.
Enterprise-grade controls supporting access management, workload isolation, auditability, and long-term stability for production-scale hybrid quantum-AI environments.
QAI collaborates with research institutions, enterprise partners, and technology organizations to deploy and operate hybrid quantum–AI systems in real-world environments.
