Problem

Teams need an independent technical view before committing to quantum access, HPC integration, hybrid workflows or a platform direction.

What we do

We run a time-boxed Architecture Review: understand the system and goals, assess architecture and risks, and deliver clear, prioritized recommendations.

Typical engagement

1–2 weeks with discovery, assessment and a review session.

Deliverables

• Discovery session
• Architecture assessment
• System context and constraints
• Technical risks
• Prioritized recommendations
• Review session

Technologies

• Hybrid quantum-classical architecture
• HPC and cloud infrastructure
• Kubernetes / workflow tooling where relevant
• QPU provider access patterns

Outcomes

• Independent technical clarity
• Shared understanding of risks
• Actionable next steps
• Better decisions before large spend

Problem

Organizations need more than access to a QPU or a Kubernetes cluster. They need controlled processes: where a workload may run, who approves costly or sensitive steps, how infrastructure is provisioned, and how execution is observed and audited.

What we do

We design and implement controlled infrastructure workflows: request → plan → policy check → approval (when required) → provision → place → execute → observe → results / cost / audit. Deterministic tooling runs the operations; policy sets boundaries; humans approve high-risk steps. QPU is a first-class target alongside CPU, GPU, HPC and simulators — not a later add-on.

Typical engagement

Architecture and implementation engagement, usually after an Architecture Review. Scope can start with one hybrid path (e.g. CPU → simulator → one QPU backend) and expand.

Deliverables

• Workflow and decision model
• Policy and approval design
• Placement and execution path
• Reference implementation or PoC
• Operational and audit notes
• Handover to client teams

Technologies

• Existing Kubernetes / HPC / cloud stacks
• Workflow and automation tooling where useful
• Simulators and QPU provider APIs
• OpenTelemetry / observability hooks

Outcomes

• One controlled path across heterogeneous compute
• Policy and approval baked into execution
• Patterns that feed the Mathnetica Platform
• Quantum included from the start — not bolted on later

Problem

Organizations need a coherent infrastructure architecture for quantum compute that fits existing cloud, HPC and platform practices.

What we do

We define constraints, target design, integration patterns, operational model and a practical roadmap your teams can implement.

Typical engagement

Multi-week architecture engagement or follow-on from an Architecture Review.

Deliverables

• Constraints and current-state assessment
• Target architecture
• Integration and operations guidance
• Technology decisions and ADRs
• Implementation roadmap

Technologies

• QPU providers and simulators
• Cloud / on-prem infrastructure
• Workflow and scheduling systems
• Observability stacks

Outcomes

• Clear technical direction
• Decisions that hold in production contexts
• Client teams equipped to own the system

Problem

Accessing a QPU is not the same as operating it inside real infrastructure — queues, credentials, results and classical stages must fit existing systems.

What we do

We design and implement critical-path integration between classical infrastructure and quantum execution environments.

Typical engagement

Time-boxed integration / PoC engagement.

Deliverables

• Integration design
• Working reference path
• Operational notes
• Handover to client teams

Technologies

• HPC / Slurm where relevant
• Kubernetes and workflow tools
• Provider SDKs and APIs
• OpenTelemetry where useful

Outcomes

• Working hybrid execution path
• Patterns client teams can extend
• Lessons that inform Mathnetica Platform research

Problem

Teams often do not know which workloads, providers or infrastructure changes are worth pursuing first.

What we do

We assess candidate workloads and current infrastructure, then recommend a realistic experiment path — without quantum hype.

Typical engagement

Short assessment, often paired with Architecture Review.

Deliverables

• Workload and infrastructure findings
• Recommended experiment path
• Risks and constraints
• Next-step options

Technologies

• Classical and HPC stacks
• Simulators and QPU access models

Outcomes

• Honest readiness picture
• Prioritized experiments
• Clear go / no-go signals