The Platform for
Quantum R&D
Spinorio helps quantum teams benchmark, inspect, and reproduce experiments across quantum SDKs, simulators, and hardware backends, turning fragmented quantum runs into structured records for better research and development in quantum computing.
Expected Release: August 2026
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A quantum-aware workspace for reproducible research
Spinorio brings inspection, tracking, benchmarking, and reproducible execution into one quantum research workspace. It turns each quantum run into a structured experiment record, capturing circuits, parameters, backends, transpilation steps, results, performance metrics, and execution context. By connecting information across SDKs, simulators, and hardware backends, Spinorio helps researchers inspect quantum workflows, compare runs, benchmark algorithms, and reproduce results more accurately and efficiently across the full quantum R&D cycle.
Supported quantum SDKs
Accelerated Quantum R&D
Quantum Workflow Intelligence
Inspection, tracking, benchmarking, and reproducible execution in one research workspace.
Quantum Experiment Tracker
Every execution in Spinorio becomes a first-class object called an Experiment. It captures the full context of a quantum run including circuit, parameters, backend, transpilation steps, and results in a structured form. This allows users to track, compare, and reproduce quantum computations across different runs and configurations inside a single workspace.
Quantum Workflow Inspection
Spinorio captures and structures quantum workflow information throughout execution in the JupyterLab environment, extracting rich context from circuits, backends, transpilation, and results. It goes beyond raw SDK outputs by connecting and enriching workflow data across stages and SDKs. It also computes derived quantum metrics that are not directly provided by SDKs, turning low-level execution data into an interpretable and unified view of the quantum workflow.
Quantum Benchmark Workflow
Spinorio enables researchers to benchmark quantum optimization algorithms against standardized problem instances inside Spinorio Lab. It automates execution, validates returned solutions, captures performance metrics, and compares results across algorithms, SDKs, simulators, and hardware backends. Each run becomes a structured benchmark record for evaluating solution quality, runtime, resource usage, and experimental context.
Build, inspect, and execute quantum workflows, from circuit design to backend-ready results, in one quantum-aware workspace.
From Circuit Design to Backend-Ready Results
Quantum Circuit Intelligence
Spinorio enhances circuit design by analyzing quantum circuits at a structural level as they are created in JupyterLab, extracting key properties beyond standard SDK outputs. It reveals entanglement structure, depth and trainability tradeoffs, two-qubit gate concentration, and structural redundancy, helping users understand efficiency and hardware impact before execution. For parameterized circuits, it provides early indicators of parameter sensitivity, making circuit behavior more predictable and easier to optimize.
Backend-Aware Transpilation
Spinorio captures how quantum circuits are transformed during execution and connects these transformations with their originating circuits and execution context. This provides a unified view of how compilation decisions and backend constraints impact the final runnable quantum workflow.
Execution & Results Inspection
Spinorio captures execution events, including simulation and backend runs, and connects results back to their originating circuits and transpilation history. This enables a continuous and reproducible quantum workflow across experiments, parameters, and backends.
Spinorio Lab · Quantum Research Workspace
Accelerate Quantum R&D
Advanced quantum R&D is difficult to manage with scattered notebooks, raw SDK outputs, backend-specific job data, and experiment results that are hard to compare or reproduce.
Spinorio brings code, circuits, parameters, transpilation, simulations, hardware jobs, benchmarks, and results into a quantum-aware workspace built on JupyterLab — helping researchers build, inspect, run, and refine quantum workflows with greater structure.
QuantumClass™
Learn Quantum Programming
QuantGates has trained professionals, students, and researchers from major organizations such as Barclays and Accenture, top universities including Yale, UC Berkeley, and the University of Illinois, and national laboratories such as the National Energy Technology Laboratory and the Pacific Northwest National Laboratory.
Learners Trained
Practical Quantum Computing
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Trusted by Researchers and Professionals from Leading Global Universities and Companies
