PRIVATE COMPUTATIONAL DEPLOYMENTS
Use the appropriate SpinForge capability in a supported customer-controlled environment. Choose CPU execution where the product supports it and acceleration where the workload justifies it.
Available products. A customer-specific workflow.
CLI · MCP · Headless
Engineering groups, enterprise-AI teams, research organizations and software vendors with private deployment requirements.
A useful implementation has a specific job. The scope is built around your original requirements, environment and acceptance criteria.
Data-handling or operational requirements may favor a deployment your organization controls.
Scope the selected product locally or in an approved private environment, with explicit data, access, dependency and support boundaries.
Some admitted tasks can run on a supported CPU path without provisioning a GPU cluster.
Match the product and model to the available execution path. UNISOLVE’s CPU reference engines, for example, do not require a GPU; other products retain their own requirements.
Authentication, updates, telemetry, optional packages and recovery still need decisions.
Document those operating requirements. Qualify any offline requirement explicitly rather than assuming that command-line availability means air-gapped operation.
The final order identifies the selected products, integration work and operating responsibilities. Included components and work are not charged again.
Selected products, model classes, hardware, runtime dependencies, user access and invocation modes.
Agreed data location, authorization, retention, deletion and handling of artifacts for the intended environment.
Installation/configuration guidance, update and rollback procedures, support ownership and accepted failure behavior.
Functional and workload-specific checks confirming that the deployment meets the agreed requirements—not a blanket compliance certification.
The team wants to call a supported CPU-based UNISOLVE operation from an authorized local client, keep the source models in its environment and retain the returned checks.
Explanation only—not a live product run or a claimed customer deployment.Confirm the task, product, hardware and optional dependencies. CPU and GPU capabilities are not assumed interchangeable.
Agree the supported models, execution environment and acceptance measures before committing to the delivery.
Choose the relevant capability.
Not every workflow needs every product.
Existing eligible software plans can cover customer-hosted use at their stated limits. Private installation, offline qualification, additional sites and managed operations require a defined quote; no dedicated hardware is included by default.
For a product and model with a supported CPU path, yes. UNISOLVE’s CPU reference engines are one documented example. Each selected tool’s actual requirements still apply.
Not automatically. Network access, authentication, licensing, dependencies, updates and telemetry must be reviewed before any offline requirement is accepted.
An operated deployment can be scoped with explicit access, responsibilities and support commitments. It is different from an ordinary software license.
Commission the model, integration and acceptance work needed for your task. Existing products stay independently available.
One capability. A connected workflow.
A team to put it into practice.