AI experimentation
Move supported machine learning workloads toward quantum execution with less framework-specific development.
All productsFrom AI code
Quantum Enablement / Compute
QuantumPortal
From AI code
to quantum execution.
QuantumPortal helps teams prepare, compare, and execute quantum workloads without mastering every hardware platform. Alongside execution, local resource estimation shows what future fault-tolerant algorithms could require.
The intelligence
Quantum compilation, hardware selection, execution, and modeled resource requirements.
An independent QuGradient product
Make quantum computing a practical next step.
Different quantum frameworks and hardware choices make adoption complex. QuantumPortal brings compilation, hardware selection, execution, and resource planning into a clearer workflow so teams can focus on the problem they want to solve.
Reduce development complexity, avoid hardware lock-in, and make informed choices about execution and future quantum investment.
From a question
to a clearer decision.
A practical workflow, with the technical detail available when you need it.
- 1
Prepare your workload
Translate supported machine learning code into quantum circuits, or explore bundled and custom programs in the resource estimator.
- 2
Understand the requirements
Estimate physical qubits and modeled runtime for future fault-tolerant hardware. Compare profiles and error-correction assumptions.
- 3
Select and execute
Choose a supported execution environment or use Auto Mode to guide selection around latency and cost, then execute the workload.
- 4
Share the planning evidence
Export resource estimates as CSV, JSON, or LaTeX for research, architecture reviews, and investment discussions.
Where it can help.
AI and machine learning teams, enterprises, quantum researchers, hardware strategists, security analysts, and educators.
Hardware and cost choices
Compare execution options while retaining flexibility across supported hardware platforms.
Long-term quantum planning
Explore resource requirements for illustrative security, chemistry, and optimization workloads before committing to future infrastructure.
The commercial relevance
A focused product.
A practical opportunity.
QuantumPortal addresses both adoption and planning: helping AI teams execute supported workloads while giving researchers and decision-makers tools to evaluate future resource needs. This creates relevance across enterprise experimentation, hardware strategy, research, and education.
Hardware-agnostic execution reduces dependence on a single platform. Auto Mode supports environment selection, while local resource estimation makes hardware trade-offs visible without requiring a hosted estimator account.
Discuss partnerships or investmentExecution and estimation, in one product
The execution workflow translates supported machine learning code into circuits and abstracts compilation, hardware selection, and execution. Auto Mode considers factors such as latency and cost. The local estimator provides Estimator, Compare, Scaling, Custom, and Export workspaces, with fifteen bundled programs and six hardware profiles spanning superconducting, trapped-ion, and Majorana assumptions.
Understand the results
Execution results and resource estimates answer different questions. Estimates model physical-qubit requirements, error-correction overhead, and runtime for future fault-tolerant hardware; they are not measured QPU results. Execution availability depends on supported workloads and environments. Export local estimates before closing the session.
QuantumPortal / Access
Start with
a conversation.
Discuss your workload with the team, explore execution and estimation options, and ask about current product access.
The dedicated product website is not yet available. Contact QuGradient to learn more or discuss access.