Fleet and delivery tracking software for things on the move

Because a tracking page that was accurate twenty minutes ago creates the support call it was meant to prevent. Customers and operations teams act on what the screen says, so a stale status is worse than none.

That makes freshness the core requirement: driver updates propagate immediately, the system shows how recent each position is, and it degrades visibly rather than silently going out of date.

Jobs are created from orders, assigned to drivers by area, capacity and availability, and pushed to the driver app with addresses, contacts and instructions. Route planning orders stops sensibly, and changes during the day reach drivers instantly instead of by call.

Operations see every vehicle and job on one screen, with exceptions, such as a late delivery or a failed attempt, surfaced first.

At each stop the driver captures what is needed: a photo, the recipient's signature or a one-time code, with time and location attached automatically. Failed attempts record the reason. The proof is available to operations and customers immediately, which settles most delivery disputes in seconds.

By recording every movement as it happens: receipts, picks, packs and dispatches are scanned against orders, and returns are checked back in. Cycle counts compare physical stock with the system regularly, so differences are found while they are small and traceable.

The driver records the reason, such as customer unavailable, wrong address or refused, with time, location and a photo where useful. The customer is notified with options to reschedule or redirect, and the job returns to dispatch for the next run automatically.

Failure reasons are reported by area and customer, which often reveals address or timing problems that can be fixed upstream.

Every vehicle's position and status, jobs by stage, deliveries running late, failed attempts, and driver performance over the day. Exceptions surface first, so the team spends its time on the deliveries that need attention rather than watching the ones going fine.

With data from the trips themselves: on-time rate, stops per shift, failed attempts by reason, and distance against the planned route. Comparing drivers only makes sense on similar routes and loads, so reports group them that way, and show where a route, not a driver, is the real problem.