Daysalvage

A field-service day can collapse when a job runs long, a technician calls out, weather changes or a part is missing. Daysalvage takes the remaining work, current capacity and customer commitments and proposes a recovery plan. The supplied research confirms a live booking agent that accounts for drive time and skills but found no AI-native day-recovery product; route optimization infrastructure is available. The wedge is post-booking disruption, not general scheduling. A solver output is a scenario, not a feasible promise, because live location, labor rules, emergency priority, parts, access windows, accessibility needs and customer consent can be stale or absent. One dispatcher may approve an exact batch, but the approval must bind the plan version, affected stops and message text; any material change invalidates it. Customers can accept, reject or fail to respond. A service provider acknowledgement is not customer confirmation or completed work. Disruption, input snapshot, solver proposal, constraint exception, dispatcher approval, customer notice, customer response, schedule command, provider acknowledgement, technician readback, arrival and service outcome remain separate. Success is faster recovery with fewer avoidable broken promises—not autonomous dispatch, guaranteed arrival windows or worker productivity scoring.

A field-service dispatcher or operations manager coordinating multiple technicians, skills, parts and customer windows each day.