Runtime support for governed physical intelligence.
Xolver Runtime keeps the public story focused on control, review, and evidence. It is not a public implementation manual.
Detailed integration material, configuration mechanics, and operating recipes are shared only through qualified partner channels.
What public readers should know
Xolver Runtime is the deployment layer that helps teams prepare, review, monitor, and improve intelligent machine workflows close to the equipment.
- AI proposals are reviewed before physical execution.
- Site, task, equipment, and operator boundaries remain explicit.
- Important behavior can run near the machine for response and resilience.
- Operational records help teams understand what happened and what should improve.
What stays qualified
Implementation details are shared directly with qualified partners after the machine, site, workflow, and safety requirements are understood.
- Private integration mechanics.
- Facility-specific setup details.
- Model, data, evaluation, and evidence methods.
- Partner-specific engagement materials and operating limits.
How evaluation starts
Teams usually begin with a scoped application review rather than a live-control claim. The goal is to understand the workflow, risks, exception paths, and review needs before an engagement advances.
- Define the machine and workflow.
- Review constraints and exception paths.
- Prepare a controlled evaluation plan.
- Use evidence from review and supervised operation to decide next steps.
Public pages explain outcomes, not recipes.
Xolver can discuss architecture, safety posture, and review needs at a high level. Specific operating methods, model handling, validation mechanics, and partner evidence packages are not public website content.
Discuss qualified access