Fleet dispatch and route optimisation, decided by AI
Jobs matched and sequenced against live driver locations, vehicle capacity, time windows and driver hours, then pushed straight to the driver.
The problem
Manual job allocation burns time and fuel. Dispatchers juggle driver locations, vehicle capacities, delivery windows and traffic across phone calls and spreadsheets. Sub optimal routing raises fuel cost and misses delivery windows, while drivers sit idle waiting on an assignment when a nearby job is open.
What gets built
A dispatch agent that takes incoming delivery jobs, aggregates live driver locations and vehicle availability, and uses Claude to match and sequence the work against capacity, distance, time windows and driver hours. Optimised routes go to drivers on WhatsApp, dispatchers watch a live job board, and any deviation or delay triggers a customer notification and a re-optimisation suggestion.
The chain, end to end
Every piece sits where your business already works. Nothing here asks your people to open a new tool.
What finished looks like
We name the finish line before we start, so there is no argument later about whether it landed.
- Standard delivery jobs allocated without a dispatcher assigning them by hand.
- Drivers receiving route assignments on WhatsApp once a job is confirmed.
- Fuel per delivery and on time rate measured against the manual routing baseline.
- The dispatcher freed from allocation to work exceptions instead.
Start with a translation, not a tool
Every engagement enters through one doorway: a diagnostic, not a tool. Begin with a free Impact Analysis, or go straight to the Diagnostic when you are ready.