Transportation and Fulfillment Optimized Concurrently Across Every Order, Every Day

Coordinate supplier pickups, consolidate inbound loads, and align raw material arrivals with production schedules — eliminating the stoppages that uncoordinated inbound causes.

Model every inbound flow — supplier origin, purchase order timing, raw material lead times, and production line sequencing requirements — and build consolidated inbound routes that maximize truck fill rates while meeting the delivery windows production depends on. Evaluate make-or-buy and carrier-mix decisions quantitatively, forecast future inbound freight volumes by mode and lane to support carrier bidding cycles, and exchange data with suppliers and 3PLs in real time through any digital interface — ensuring inbound transportation and procurement planning operate from the same plan rather than two disconnected systems.

Plan the movement of finished goods from the central warehouse to regional DCs as a single integrated decision — not a routing exercise run after the replenishment plan is already fixed.

Automate concurrent planning of priority-based order fulfillment and outbound transportation, align production to maximize truck fill rates, and coordinate inbound runs with optimal production sequence. Build multi-stop, multi-modal, and multi-day outbound routes from the central warehouse to regional DCs with full visibility to delivery time windows, complex tariff structures, dedicated fleet constraints, and hours-of-service regulations. When the replenishment plan changes — due to a demand shift or a supplier disruption — the outbound transport plan recalculates automatically, keeping load consolidation and route efficiency intact without a manual re-planning cycle.

Plan the daily movement from the distribution centers to the stores with the route density, vehicle utilization, and delivery window precision that last-mile economics demand.

Model every DC-to-store delivery leg against store-level receiving windows, vehicle capacity constraints, route geography, delivery frequency policies, and replenishment work order priorities — building optimized daily routes that maximize drop density and vehicle utilization while meeting the in-store availability commitments the replenishment plan requires. Exchange work orders and delivery confirmations with WMS systems automatically, track delivery performance against service level targets in real time, and feed actual delivery outcomes back into route planning to improve schedule accuracy progressively — turning the most cost-intensive and time-sensitive leg of the supply chain into a manageable, data-driven operation.

Solve fulfillment and transportation as a single optimization problem across fulfillment and transportation decisions — then compare objective functions side by side before committing to a plan.

Rather than optimizing fulfillment first and routing second, Solvoyo’s concurrent optimization engine solves both simultaneously — encoding inventory priorities, vehicle capacity, delivery windows, carrier costs, and service level targets into a single model and producing a plan where every fulfillment decision is aware of its transportation consequences, and every routing decision is aware of the inventory it must serve.

Run the same scenario against multiple objective functions in parallel:

• Maximize OTIF — prioritize service level performance across all deliveries, accepting higher transportation cost where necessary to protect on-time, in-full commitments.
• Minimize Cost — identify the lowest-cost fulfillment and routing configuration that still satisfies service level floor constraints, surfacing structural savings opportunities that routing-only tools cannot see.
• Balanced Scenario — optimize across a weighted combination of cost and service objectives simultaneously, producing the efficient frontier between the two extremes and quantifying the cost of each additional percentage point of OTIF improvement.
• Custom Scenarios — modify any input parameter directly: change delivery frequency, adjust vehicle mix, shift carrier allocation, override service level targets for specific store clusters, or model a network change such as a new DC or a route restructure — and generate a fully optimized plan for that configuration in minutes. Compare the custom scenario against the standard objective functions on the same screen, with cost and service metrics shown side by side, before authorizing the preferred plan into execution.

Connect fulfillment priorities, transportation decisions, and real-time network visibility on one platform — so every movement serves the service level target, not just the routing algorithm.

Exchange data and intelligence with multiple sources — ERP, WMS, TMS, and CRM for enterprise data, as well as embedded sensors on trucks, navigation devices, and package tracking services — to maintain a live view of every active shipment across all three transportation legs simultaneously. Track OTIF rates, truck utilization, cost per delivery, and route adherence continuously against plan, and surface performance gaps as actionable exceptions before they become customer service failures or carrier penalty events.

Detect supply chain disruptions as they emerge across all three transportation legs — and receive prioritized, prescriptive actions before the disruption reaches the shelf.

With Solvoyo’s AI agent Solvi, continuously monitor every signal that indicates the active plan is at risk — supplier OTIF degradation, inbound late arrivals, vehicle breakdowns, severe weather events closing routes or restricting access, DC throughput constraints, and demand spikes outpacing current delivery schedules. Classify each deviation by its downstream service and cost impact, rank exceptions by urgency, and attach a prescriptive corrective action — reroute around weather-affected corridors, resequence stops, substitute carrier, expedite inbound, reallocate DC inventory — before the disruption compounds. Forward-looking pattern recognition also flags developing risks before they fully materialize, converting disruption response from reactive fire-fighting into a managed, exception-driven planning workflow.