video1.0<iframe src="https://www.loom.com/embed/596df6cf06c54121b8a50d3ae3a8d22f" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/596df6cf06c54121b8a50d3ae3a8d22f-1e2e90226163a931.gif299.075This Loom prototype explains how Hexalog can automate exception flow handling for shipments that get stuck. The author describes reading public sources, identifying that last mile already manages exceptions but relies on people to open multiple systems and lose 2 to 3 hours each time, and then building a control tower dashboard for scaling issues. They use a taxonomy to prioritize exceptions based on frequency and money involved versus impact if wrong, an exception module with likely root causes, evidence trails, confidence, SLA at risk, and recommendation plans with boundaries for six smaller agents. The loop includes approval, execution with verified outcomes, evaluation using eight parameters where human override rate is a fail criterion, scenario simulation, and an estimated ROI of saving 230 hours and 4.2 lakhs per 100 cases, with progressive autonomy from observe to optimize.