For a logistics network · operations
Where should the next depot open, and which route reaches the most people?
Coverage and tour intelligence — the agent proposes, field reps verify.
Today coverage and routing calls lean on spreadsheets, local gut-feel or heavy GIS software — slow to explore the options.
Why now logistics margins are thin, and AI can weigh coverage and routing far faster than a spreadsheet.
Use cases Logistics & delivery, field sales, retail expansion, utilities.
Interactive demo ↗The question
A delivery network can’t see its own gaps. Where is demand going unserved, and would one more depot actually help?
The approach
Map current coverage over real order density, find the highest-value under-served clusters, and propose where a new depot would lift the most reach.
The feature
From a proposed depot it plans an optimized multi-stop tour — and field reps call to confirm the clusters, so a human checks the model before anything moves.
Function
The coverage map
Order density, current reach and depots over the network — the gaps are where demand outruns coverage.
Function
The agent proposes, a rep confirms
Every proposal is checked by a person on the phone before a depot moves — the human stays in the loop.