Empty-Mile Backhaul Matching
A private fleet or contracted truck that delivers an outbound load usually drives back empty, because matching that return leg with available backhaul freight requires checking multiple load boards, known partner freight, and internal cross-dock opportunities against the truck's actual route and timing — a coordination task that's tedious enough at scale that most fleets just accept the empty return as a cost of doing business rather than actively working every leg. Those empty miles are pure cost with zero revenue, and across a fleet running regular routes, the accumulated waste is substantial even though no single empty leg looks like a big deal on its own.
STARTING PRICE
From €799
Complex tier · Multi-system orchestration, custom logic, and higher-volume or higher-risk processing.
Get a quote →Saves roughly 5-8 hrs/week for a fleet dispatch or logistics team, plus direct fuel and mileage cost reduction.
How the automation works
We match outbound delivery routes against available backhaul freight — from load boards, known partner and broker freight, and internal cross-dock or transfer needs — automatically as routes are scheduled, checking timing compatibility, equipment type, and whether the backhaul's pickup and delivery points actually fit the truck's return path without a costly detour. Viable matches get surfaced to dispatch with the backhaul rate and the net effect on total route profitability, so a marginal backhaul that adds more detour cost than it earns gets filtered out automatically rather than accepted just because it's better than nothing. Matches booked feed back into route planning, building a record of reliable backhaul lanes worth pursuing proactively rather than opportunistically.
Process flow
- 01
Outbound route data syncs trigger
Scheduled outbound delivery routes sync in with destination, expected completion time and equipment type.
- 02
Search backhaul sources integration
Available backhaul freight is searched across connected load boards, known partner/broker freight, and internal cross-dock transfer needs near the delivery destination.
- 03
Match timing and equipment ai
Candidate backhauls are matched against the truck's expected free time, equipment type, and whether pickup and delivery points fit the return path without a costly detour.
- 04
Evaluate net route profitability ai
Each viable match is evaluated on net effect to total route profitability — backhaul rate minus any added detour cost — filtering out matches that cost more in deviation than they earn.
- 05
Surface to dispatch output
Qualifying backhaul matches are surfaced to dispatch with the rate, pickup window and net profitability impact, ready for a quick booking decision.
- 06
Build reliable lane history output
Booked backhauls feed a lane history, identifying return routes with consistently available freight worth pursuing proactively rather than searching fresh each time.
Inputs
- Scheduled outbound route data
- Load board and broker freight feeds
- Internal cross-dock/transfer freight needs
- Equipment type and driver hours availability
Outputs
- Matched backhaul opportunities with rate and timing
- Net route profitability estimate per match
- Booking-ready dispatch recommendation
- Reliable backhaul lane history
Works with
Prefer a fully custom build instead of an off-the-shelf integration? We scope both options during your free consultation — most jobs like this one work fine on standard connectors, but higher-volume or non-standard systems sometimes need bespoke API work, reflected in the complex tier.
Where this goes wrong if you get it wrong
- A backhaul that pays a decent rate but requires enough detour to add real miles and time can quietly cost more than it earns once fuel and driver hours are factored in — matching has to evaluate net route profitability, not just the backhaul rate in isolation.
- Matching purely on destination proximity without checking driver hours-of-service remaining can create a backhaul assignment the driver legally can't complete without an unplanned rest stop — timing matches need to account for actual remaining drive-time availability, not just calendar availability.
- Equipment type mismatches (a flatbed backhaul matched to a dry van truck) look like a fit on lane and timing alone but aren't executable — matching needs an equipment compatibility check as a hard filter before a backhaul is surfaced as viable.
- Chasing every marginally profitable backhaul regardless of freight reliability (a load board posting that frequently falls through) erodes trust in the matching system after a few no-shows — match sourcing needs a reliability weighting that favors known partner freight and proven load-board posters over unverified one-off postings.
Frequently asked questions
Does this account for driver hours-of-service limits?
Yes — matches are checked against remaining legal drive-time availability, so a backhaul isn't surfaced if completing it would require exceeding hours-of-service limits.
What backhaul sources does it search?
Connected load boards, known partner and broker freight relationships, and internal cross-dock or inter-facility transfer needs near the delivery destination.
How does it avoid a backhaul that costs more than it earns?
Every match is evaluated on net route profitability — backhaul rate minus added detour miles and time — not just the headline rate, so detour-heavy matches that lose money get filtered out.
Does it prioritize reliable freight sources over one-off postings?
Yes — a lane and source reliability history builds over time, weighting known partner freight and proven posters above unverified one-off load-board listings.