Supply Network Flow Stabilization
No service failures. No high-cost carriers.
No surprises.
Not just a compliant plan — the best possible deployment schedule for every lane, every week. Smoothed, space-and-labor-constrained, cost-effective. For ~30 days out.
Makes your current TMS, WMS, ERP, and APS work together. No silos. No rip-and-replace.
Your APS plans inventory. It doesn't plan what the network can absorb. LevelLoad builds a 30-day capacity-constrained deployment schedule that smooths daily volumes, locks in preferred carrier commitments early, and produces a plan the network can actually execute — cost effectively.
A digital twin of your network — planning 30 days out against real constraints.
Traditional transportation planning reacts to demand. LevelLoad solves the entire deployment schedule as a single optimization problem — every lane, every carrier, every site, every day.
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60% lessDaily shipment variability — the primary driver of spot dependency and OTIF failures
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97%First tender acceptance — preferred carriers commit when volumes are predictable
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~4%Replenishment freight savings — from core carrier commitment and eliminated spot premiums
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OTIF fixedVariability reduction eliminates dock congestion that cascades into OTIF supply chain failures
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4 monthsTo positive ROI — implementation ~120 days; savings compound as carrier relationships stabilize
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30 daysPlanning horizon — reserve carrier capacity weeks ahead, not last-minute at spot rates
End-of-Week Bunching Becomes End-of-Month.
When APS systems trigger replenishment by inventory threshold, shipments pile up at end of week. Carriers reject. Trucks run empty. OTIF fails — and it was all predictable 30 days earlier.
Four steps from volatile to predictable.
LevelLoad reads data from APS, ERP, TMS, and WMS simultaneously — building a deployment schedule that respects every physical constraint before committing to ship.
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Constraint ingestion
Dock throughput, carrier capacity, warehouse labor, and lane balance across the full network — all ingested simultaneously.
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30-day horizon planning
Volume smoothed across lanes weeks in advance — giving carriers the lead time to commit preferred capacity before spikes happen.
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Days-of-supply prioritization
Sites running shortest inventory get served first. Deployment sequences by criticality, not just order dates.
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Continuous re-planning
The plan updates as reality changes. Exceptions surface before they become misses — not after the OTIF failure.
End-of-Week Bunching Becomes End-of-Month.
Without LevelLoad
- End-of-week bunching — 60–80% of weekly volume ships Thursday/Friday
- Carrier rejection at peak — preferred carriers full, spot trucks at 2× the rate
- Reactive planning — transportation team chasing trucks that should have been booked weeks ago
- OTIF failures from dock congestion — cascading into detention, overtime, and customer penalties
With LevelLoad
- 60% less daily variability — volumes smoothed across every lane, every week
- 97% first tender acceptance — preferred carriers commit with 30-day visibility
- Proactive planning — exceptions surface before they become misses, not after
- ~4% freight cost savings — from core carrier commitment and eliminated spot premiums
Real companies.
Measured results.
Deployed across multiple continents. 5,000+ truckloads per year minimum. Supply network stabilization at scale.
Shipment spikes were destroying carrier planning across all of North America.
Unpredictable order bunching from manufacturing plants created costly spikes in carrier demand. Transportation planning was constantly reactive — securing trucks last-minute at premium rates.
"AI in supply chain management is not a future aspiration — it's a present reality."Scott DeGroot, VP Global Logistics, Kimberly-Clark
Rising fuel, driver shortages, and poor utilization were inflating costs and emissions.
Trucks running at 90–95% looked acceptable. At hundreds of daily shipments, the gap cost millions and threatened a 2030 Scope 3 emissions target. Network flow stabilization fixed both simultaneously.
"Efficiency and sustainability are not in conflict."— ProvisionAI Case Study, 2025
America's largest rice processor was leaving money in every trailer.
Mixed product weights meant trucks hit axle limits before filling — heavy 20 lb bags exhausting capacity before lightweight cups could fill the cube. AutoO2 solved both the load and the planning problem.
"The increase in weight per truck adds up in terms of cost savings."Zachary Dale, Supply Chain CI Manager, Riviana Foods
Ready to stop planning volatility and start preventing it?
Talk to our team and see how LevelLoad fits into your operation — no rip-and-replace, no lengthy onboarding.
Contact SalesOr reach us at info@provisionai.com
