Provisioning has become one of the most underestimated cost drivers in modern IT environments. While organizations often focus on hardware acquisition, licensing, or cloud spend, the majority of provisioning cost accumulates over time through labor, rework, downtime, and operational inefficiencies that intensify as fleets grow.

Traditional provisioning models built around static images, manual workflows, and tightly coupled processes do not scale cleanly. As device counts increase, image variants multiply, maintenance effort grows, re-imaging cycles become more frequent, and reliance on specialized personnel increases. What begins as a manageable process gradually becomes a structural cost problem.

Provisioner was designed to address this challenge by modernizing the provisioning layer itself. By replacing static imaging with a software-defined, just-in-time provisioning model, organizations can significantly reduce operational overhead while improving consistency and control. Automation replaces manual effort, recipes replace images, and devices are built or rebuilt only when needed.

In practice, this approach reduces the ongoing cost of image maintenance, minimizes re-imaging and remediation effort, lowers dependency on skilled labor, and shortens deployment and recovery timelines. When these efficiencies are applied across the full lifecycle of a device fleet, organizations commonly achieve up to a 50% reduction in total cost of provisioning ownership.

Lower cost is not the result of reduced capability or increased risk. It is a byproduct of better architecture that decouples provisioning from rigid workflows, people-dependent processes, and legacy assumptions. The result is more predictable economics, faster deployments, and greater operational flexibility at scale.

If provisioning costs continue to rise as environments grow, the issue is not scale itself but the provisioning model supporting it.