AI that gets the freight there on time
Route, fleet and ETA intelligence that catches delays before they cascade across the network — proactive risk detection that holds 96.4% on-time delivery.
A Hominis app module · your transportation & logistics data, app-ified
Catch the delay before it cascades
Route, fleet and ETA intelligence on a live network graph.
Dynamic route optimization
Re-plan routes against live traffic, weather and capacity instead of static plans built the night before — solving the network you actually have, not the one on paper.
Re-optimized continuously, not nightly
ETA-risk prediction
Score every shipment for the probability it slips its window, days out — so dispatch intervenes on the at-risk 5% instead of firefighting after the miss.
96.4% on-time delivery sustained
Network-wide delay propagation
Model how one late leg ripples through downstream hubs, transfers and last-mile so you reroute around a bottleneck before it becomes a backlog.
Cascade caught upstream, not at the dock
Fleet & asset utilization
Match loads, trucks and drivers against demand to cut empty miles and idle assets — the difference between a full backhaul and a deadhead.
Deadhead and dwell flagged in real time
Demand & capacity forecasting
Forecast lane-level volume and capacity so you pre-position equipment and book carriers ahead of the surge instead of paying spot rates into it.
Lane-level, not regional averages
Reasons over the whole network, in the open
What won adoption in the control tower.
Built on the live network graph
The LogisticsNetwork instrument models lanes, hubs, carriers and shipments as one connected graph — so a prediction reasons over the whole network's state, not an isolated shipment. That topology is what makes propagation visible before the delay lands, and it is hard to rip out once dispatch runs on it.
Decisions dispatch will actually act on
Every ETA-risk score surfaces the drivers behind it — the late transfer, the closed lane, the weather front — so a dispatcher trusts the alert enough to reroute. Explainable risk, not a black-box flag, is what won operational adoption in the control tower.
One method, tuned for transportation & logistics
Assess, Transform, Sustain — the cycle every organization runs, dropped one level deeper for your sector's pains and sticky aspects.
Assess
Map the network graph and rank where on-time delivery actually leaks
We ingest TMS, telematics, carrier EDI and historical exception data into one network graph, then trace where on-time performance leaks — the chronic lanes, the fragile transfer hubs, the carriers that miss windows under load. The output is a ranked list of delay sources by volume and dollar impact, plus the integration map to fix them, in 4–6 weeks.
Transform
Route-optimization and ETA-risk models wired into dispatch and the control tower
We build lane-aware route-optimization and ETA-risk models on the LogisticsNetwork instrument and wire them into your dispatch and control-tower workflows — from pilot on a single corridor to hardened production across the network. The scores arrive where dispatchers already work, with the risk drivers attached, so intervention happens before the miss rather than after.
Sustain (AIOps)
Retrain against seasonal lanes, carrier drift and disruption so on-time holds
Freight networks drift — peak season, new carriers, port congestion, fuel and weather regimes all move the baseline. We monitor model performance against live on-time outcomes and retrain on your operational rhythms, so prediction quality holds through surge and disruption instead of decaying the first time the network changes shape.