PERFORMANCE & RELEASE CHECKS
Make performance and quality evaluation a repeatable part of your release process. Compare an agreed workload before a change is accepted into production.
Available products. A customer-specific workflow.
CLI · MCP · Headless
Inference engineers, numerical-software vendors and platform teams whose releases can change speed, cost, quality or resource use.
A useful implementation has a specific job. The scope is built around your original requirements, environment and acceptance criteria.
An improvement in one component can be offset by data movement, integration overhead or another part of the pipeline.
Evaluate the agreed end-to-end workload alongside the relevant component measures. Compare equivalent quality and operating conditions rather than only the strongest timing.
Model, hardware, data and dependency changes can make a comparison misleading.
Identify the accepted baseline, environment and workload revision. Keep comparability checks and variance-aware acceptance criteria in the report.
A one-off optimization result does not tell the team what happens at the next release.
Integrate a supported CLI or headless evaluation into the customer’s existing workflow, with agreed reporting and a customer-controlled review or release decision.
The final order identifies the selected products, integration work and operating responsibilities. Included components and work are not charged again.
Accepted workload, data, quality requirements, hardware/software configuration and a recorded comparison procedure.
The selected product checks connected to an existing CI or scheduled workflow, within explicit execution limits.
Performance, resource, quality and applicable correctness measures, with variance and non-comparable results kept visible.
Report artifacts, threshold rules and ownership of approvals, exceptions and rollback. Further engineering is optional.
Before accepting a new model or cache configuration, an inference team runs the same representative requests under the agreed quality and latency targets.
Explanation only—not a live product run or a claimed customer deployment.Pin the workload and conditions. Agree the metrics, repetitions and changes that require human review.
Agree the supported models, execution environment and acceptance measures before committing to the delivery.
Choose the relevant capability.
Not every workflow needs every product.
A workload assessment is $15,000 and a focused sprint is $30,000 within their existing scopes. Ongoing software access, execution infrastructure and continuing engineering are separate unless expressly included in one agreement.
No. The intended delivery connects supported product operations to your existing pipeline or scheduler. The integration and runner environment are confirmed in scope.
Your team decides the release policy. Observation mode, review-required mode and a formally authorized gate are different deployment choices.
No. This evaluates changes in the customer’s workload. Defects covered by the software license remain part of product support.
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.