Qoro Quantum has developed middleware that automates the routing of quantum circuits to multiple quantum processors and simulators, aiming to simplify access and improve resilience for users working with diverse quantum hardware and high-performance computing environments
Qoro Quantum, a company founded in 2024 and incorporated in the UK and Germany, has introduced a middleware platform designed to streamline the deployment of quantum algorithms across a range of quantum processors and classical simulators. The company's approach centers on abstracting hardware-specific details from users, allowing researchers and developers to focus on algorithm design rather than device integration or backend selection. This strategy is intended to address the growing complexity of quantum computing environments, where multiple hardware platforms and simulation methods coexist.
Middleware Architecture
The core of Qoro Quantum's offering is the Divi SDK, a software development kit that accepts optimization problems-such as quadratic unconstrained binary optimization (QUBO), higher-order unconstrained binary optimization (HUBO), and variational algorithms-and automatically generates, serializes, and parallelizes large numbers of quantum circuits. The SDK is designed to eliminate the need for users to write their own transpilation or scheduling code, instead automating the process of preparing circuits for execution on a variety of backends.
Qoro's orchestrator component is responsible for selecting among twelve different simulation methods, including stabilizer, tensor network, Pauli propagation, and matrix product state (MPS) approaches, running on either CPUs or GPUs. When hardware execution is required, the orchestrator can dispatch circuits to quantum processing units (QPUs) from any supported vendor. The selection of simulation or hardware backend is determined automatically based on circuit properties, rather than user preference, with the aim of optimizing performance and resource utilization.
Integration with HPC and Quantum Hardware
Rather than replacing existing high-performance computing (HPC) schedulers, Qoro's middleware is designed to integrate as a plugin with established systems such as SLURM. This allows quantum workloads to be managed alongside classical jobs within familiar HPC environments. In a recent proof-of-concept deployment at the Galician Supercomputing Center (CESGA), Qoro's platform was connected to fifteen compute nodes configured to mimic a distributed quantum network. Over the course of the pilot, between 15,000 and 20,000 quantum circuits were executed remotely, with secure integration reportedly completed in about one day.
Qoro's approach relies on hardware vendors' own transpilers for device-specific compilation, positioning the middleware as an automation and routing layer rather than a solution to hardware-level compilation challenges. This design choice reflects the current fragmentation of the quantum hardware landscape, where each vendor maintains its own stack and interface.
Resilience and Multi-QPU Access
A key argument advanced by Qoro Quantum is that access to multiple QPUs-across different vendors and modalities-is already a practical requirement for resilience and fallback, not merely a future scaling consideration. The company points to recent outages affecting single-vendor quantum resources, such as IBM's cloud-accessible QPUs, which left users unable to run quantum workloads until service was restored. By enabling seamless switching between available quantum processors and simulators, Qoro aims to reduce downtime and improve reliability for users operating in research and enterprise settings.
This focus on multi-QPU integration aligns with broader trends in the quantum industry, where interoperability and cross-platform access are increasingly seen as necessary for both scientific progress and commercial adoption. Similar themes have emerged in other recent collaborations, such as the partnership between IonQ and Sandia National Laboratories to develop and test trapped-ion quantum hardware for security applications, as reported in a recent Science Report article.
Developer Experience and Educational Impact
Qoro Quantum also emphasizes the potential benefits of its middleware for education and workforce development. By reducing the complexity of quantum programming and providing a unified interface for circuit generation and execution, the platform is intended to lower barriers for students and researchers learning quantum algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) and other variational methods. The company claims that its tools can reduce the amount of code required for certain workflows from tens of thousands of lines to just a few dozen, though independent verification of this claim is not yet available.
As of 2026, Qoro Quantum employs around ten full-time staff and has recently completed a pre-seed funding round. Its product offerings include a pay-as-you-go cloud platform, dedicated infrastructure services for enterprise customers, and on-premise integration solutions for HPC centers. The company's roadmap includes further development of its middleware and expansion of supported hardware and simulation backends.
Quantum middleware refers to software that sits between user applications and quantum hardware or simulators, managing tasks such as circuit compilation, scheduling, resource allocation, and backend selection. Unlike hardware-specific toolchains, middleware platforms aim to provide a consistent interface across diverse devices and simulation methods. This abstraction can simplify development and improve resilience, but it does not address underlying hardware limitations such as qubit fidelity, coherence time, or error rates. As quantum computing infrastructure becomes more heterogeneous, middleware is likely to play an increasingly important role in enabling practical research and application development, though its effectiveness will depend on continued progress in both hardware and software integration.
