AI-performance assessment software that profiles a workload, prioritizes optimization changes and checks their effect on model quality.
See what it solvesTHE PRODUCT, IN PRACTICE
Optimization is only useful when the workload improves without violating the quality requirements that matter to the application. SpinProof connects workload profiling to a ranked plan, identifies changes unlikely to help, and evaluates proposed changes against predefined data and tolerances. The resulting record makes the decision reviewable rather than leaving the team with an isolated speed figure.
A team can spend time trying changes that do not address its actual bottleneck.
SpinProof profiles the workload and produces a ranked action plan, including recommendations for changes that are unlikely to help.
A faster configuration may change outputs in ways that a timing-only benchmark does not show.
The product evaluates the change against predefined data and quality tolerances before reporting the associated performance result.
An evaluation without a clear record of its model, environment and controls is difficult to use in a release review.
SpinProof retains re-verifiable evaluation records that connect the tested artifacts and conditions to the reported result.
The product scope below describes the capability and outputs to confirm for your release. Custom integration, operated delivery and additional engineering are separately agreed.
Information about the bottlenecks relevant to the supported workload.
Candidate actions and a list of changes unlikely to help.
Quality checks and performance measurements under the agreed conditions.
Records of the tested artifacts, environment, controls and evaluation results.
SpinProof is fully available with CLI, MCP and headless access. Use the interface that fits your terminal, your agents or your automated workflow.
Run the product from a terminal or script, alongside the tools your team already uses.
Get CLI accessConnect MCP-compatible clients and agents to the product’s exposed capabilities.
Get MCP accessOperate without a graphical interface in unattended, scheduled or pipeline-driven work.
Set up headless accessProduct-specific inputs, hardware requirements and result guarantees still apply. An access mode does not change your license or deployment scope.
Explore all product interfacesA serving team is considering a supported precision or cache-compression change but must retain an accepted quality level.
Illustrative use of the supported scope, not a customer case study or a measured result.Fix the model, representative evaluation data and tolerance requirements.
Evaluate the candidate change and measure its performance under those controls.
Use the resulting report to accept, reject or revise the deployment choice.
Explore the product workflow, from your input to a result you can use.
Profile the workload to understand the kind of bottleneck it encounters.
Interactive explanation. This illustration does not execute customer workloads or display measured performance.
ML-platform teams, inference providers and engineers approving model or runtime optimization changes.
CLI, MCP and headless access are all available. Run from a terminal or script, connect an MCP-compatible client, or use the product without a graphical interface. Choose the mode during onboarding and receive its setup instructions. Runtime requirements and supported operations remain product-specific.
A receipt establishes the recorded evaluation and artifact integrity, not universal model equivalence or external certification. A separate solver’s mathematical proof and SpinProof’s model-performance evaluation answer different questions.
The agreed SpinProof release, its supported interfaces and outputs, the applicable checks and the support stated in your order. The plan defines users, workflow, environment and capacity. Source-code transfer, unrestricted redistribution and bespoke engineering are not automatically included.
Request a scoped engineering or operated-service proposal. It identifies what our team delivers, where the workload runs, infrastructure costs, acceptance requirements and ongoing support. Your software subscription alone does not activate a hosted runtime.
Explore engineeringAgree the model or workload, current baseline, environment, required output and acceptance tests. Evaluate the selected release against those conditions. A product description or a test count does not establish a gain on a different customer workload.
Plan an integrationOne named production deployment. Shared engine rights for this application included.
Scope & packagesBring a representative workload and the result your team needs. We’ll define the product, deployment and engineering scope around that task.
Activate this capability inside a qualified ai serving workflow. Compatible methods and required shared checking are included once within that workflow; the product remains independently purchasable.
Capacity, release, environment, result contract and operating responsibilities are specified before activation. Choosing an additional method is not permission to add an unrelated workload or unqualified deployment.
Explore AI Serving Choose workflow capacityCommission the model, integration and acceptance work needed for your task. Existing products stay independently available.
Use the software directly or ask us to scope the implementation.
One capability. A connected workflow.
A team to put it into practice.