At BackOps, we’re building an AI resolution layer for companies that make or move physical goods. It improves and executes internal processes across systems, internal teams, and external parties, helping them improve operating margins, complete work faster, and provide more reliable service.
Companies that make or move physical goods depend on internal processes that span systems, internal teams, and external parties. Requirements vary, conditions change, and people must gather information, coordinate decisions, complete manual steps, and follow up with everyone involved. Critical knowledge may remain concentrated with a few experienced operators, making processes difficult to standardize, scale, and improve. Work slows, operating costs rise, customer commitments are put at risk, and recoverable value is left on the table.
This is the Resolution Gap: the distance between identifying an operational need and achieving the required outcome across the systems, internal teams, and external parties involved.
AI can now synthesize information, communicate, and take action. But general-purpose AI does not arrive knowing the supply-chain process or the resolution patterns that improve outcomes. Teams must still capture and improve the real process, connect it across company systems and third-party portals, define rules and approvals, test it, and keep it working as interfaces change. That slows time to value and creates an ongoing maintenance burden.
