Spinorio Lab · Quantum Research Workspace

Accelerate Quantum R&D

Quantum research often becomes fragmented across notebooks, SDKs, simulators, hardware backends, and separate analysis tools, making experiments harder to manage, compare, and reproduce.

Spinorio brings the full workflow into a quantum-aware JupyterLab environment, helping researchers manage and analyze experiments, run agentic benchmarks, optimize transpilation with AI, and preserve the context needed for structured, reproducible quantum R&D.

Workflow inspection
Experiment tracking
Benchmark execution
Reproducible research

Supported quantum SDKs & research environment

Qiskit
PennyLane
AWS Braket
TKET
JupyterLab
Request Early Access

Initial release planned for September 2026.

Quantum workflow illustration

Accelerated Quantum R&D

A structured environment for quantum research workflows.

Spinorio is designed for researchers and developers working across complex quantum workflows that extend beyond a single notebook or SDK. It brings workflow management, benchmarking, transpilation analysis, execution history, and experiment context into one quantum-aware environment.

By preserving the relationships between circuits, parameters, compiler decisions, backends, benchmark runs, and results, Spinorio makes experiments easier to inspect, compare, reproduce, and evaluate across the research process.

Quantum R&D Intelligence

Spinorio

Understand. Benchmark. Optimize.

Understand

Quantum Workflow Management & Analysis

Manage logical circuits, transpilation artifacts, jobs, and results with complete provenance and lineage, plus deterministic workflow metrics and analysis across the research lifecycle.

Benchmark

Agentic Benchmarking

Automate reproducible benchmark workflows across algorithms, standardized problem instances, SDKs, simulators, and supported backends, with structured comparisons and reports.

Optimize

Transpilation Intelligence

Generate, compare, and evaluate transpilation candidates using standard, AI-assisted, and Spinorio-native strategies against backend-aware optimization objectives.