Route optimization alongside FourKites

What FourKites ships today

FourKites is comprehensive on the multi-modal visibility side. Several of its surfaces feed the delivery problem at the edge, but none of them are own-fleet route optimization.

• Multi-carrier in-transit tracking. Carrier-side feeds and the FourKites driver tracking app give shippers a live view of loads moving across OTR, ocean, rail, air, intermodal, drayage, parcel and last-mile carriers.
• Predictive ETAs. Recalculated as carrier loads progress; useful for inbound-to-depot planning and customer ETA communication on carrier shipments.
• Yard and dock visibility. Dynamic dock scheduling, gate moves, yard inventory. Internal-facing operational visibility.
• Shipper dashboard and exception management. Internal-facing view of all shipments with exception rules and alerts on carrier-side events.
• REST API and webhooks. Programmatic access to shipment status, milestones and exception events for downstream consumers (TMS, OMS, BI).

FourKites was not built to be an own-fleet routing engine, and the surfaces above are the right tools for what they cover. Where FourKites stops is the route plan itself, the order each stop runs in, and the constraint set an own-fleet optimizer enforces.

What real route optimization actually models

Constraint-aware route optimization is a distinct problem from stop sequencing or warehouse picking. The optimizer has to model the truck, the road, the customer, the driver and the SLA, all at once.

• Vehicle capacity. Weight, volume, pallet count, refrigerated space, hazmat zones. Different vehicles in the fleet carry different mixes of items.
• Time windows. Customer-confirmed delivery windows. Store opening hours. Driver shift bounds. School-zone restrictions. Loading-bay availability at the depot.
• Multi-stop sequencing. Hundreds of stops per truck per day. The order matters: a poorly sequenced 40-stop route adds 30%+ drive time over an optimal one.
• Multi-depot. Several depots, branches or cross-dock locations. The optimizer chooses which depot loads which truck for which stops.
• Multi-day. Long-haul routes and recurring service programs that span days. Overnight stops modeled directly.
• Skills and SLAs. Certain customers require a driver with a specific cert. Certain stops have a contracted SLA that can’t be missed.
• Dynamic re-optimization. A canceled stop, a no-access visit, a late driver. The plan re-optimizes on the fly without breaking customer-confirmed slots.

None of this is what FourKites is designed to do. It is a separate workload that needs its own engine.

Where FourKites users land today without a routing layer

Three patterns are common in FourKites customers that haven’t yet added an optimization layer. None scale cleanly past 50+ in the field, multi-depot, or recurring patterns.

• Spreadsheets and manual planning. A planner exports the day’s open orders to Excel each morning, groups them by region and vehicle, sequences stops by hand, prints route sheets. Works at small scale, scales linearly with the planner’s hours, breaks at the first big day or the first planner sick day.
• Basic stop sequencer. A point tool that orders the stops once vehicles are pre-assigned. Does not balance load across vehicles, doesn’t respect customer time windows beyond a soft sort, doesn’t handle multi-depot. Better than spreadsheets, still not optimization.
• External routing tool with manual copy-paste. Plan in Tool A, rekey the result alongside FourKites. Disconnected. The route is correct on Monday morning and out of date by Monday afternoon when the first order cancels.

The path forward is a routing layer that connects to the order system in the middle, plans against real constraints and dispatches the route through its own driver app. That is the role eLogii plays. FourKites stays as the carrier-visibility layer on its side.

How eLogii does route optimization

eLogii’s optimizer is built around two engines and six configurable modes, all callable via REST. The planner sees the rules in their dispatch desk and can adjust them; the optimizer doesn’t hide behind a black-box ML score.

• Two engines. The Default engine optimizes 100 tasks in under 10 seconds for high-throughput daily planning. The Advanced engine takes more factors into account and is the choice for multi-depot, multi-day, long-haul and constraint-heavy operations.
• Three assignment modes. Optimize Everything (creates fresh routes including all assignments), Add to Routes Keep Existing Assignments (incorporates new tasks into existing routes while preserving driver assignments), and Add to Routes Keep Existing Assignments and ETAs (inserts new tasks into available slots without modifying existing stop sequences or ETAs).
• Three load-balancing modes. Most Efficient Routes (fewest vehicles), Balance the Minimum Number of Routes (across load, time, distance or job count), and Use All Vehicles Finish as Soon as Possible (maximise speed across the fleet).
• Multi-day and long-haul. Plan a single day or an entire month in one run; multi-day routes with overnight stops modeled directly.
• Multi-depot. Route across multiple depots, branches or home start locations in a single optimization run. Each depot is modeled in eLogii from the order system.
• Recurring patterns. Task and route template groups: weekly, monthly, quarterly, bespoke cadences modeled at the data layer, not bolted on at scheduling time.
• Rule-based re-optimization. Operator-visible rules; live re-optimize while protecting locked SLAs and customer-confirmed slots.

How the integration sits alongside FourKites

The combined deployment leaves FourKites in place on its side of the stack. eLogii’s integration is with your order system, not with FourKites directly.

1. Read from the order system. eLogii pulls open delivery orders, customer master and vehicle / driver / depot data from your upstream order system (ERP, TMS or OMS). Pull on a schedule or push via webhook on order approval.
2. Optimize in eLogii. The optimization run produces routes with vehicle assignments, stop sequences, ETAs and any cross-day constraints honored. Planner reviews in eLogii’s dispatch desk or accepts an Auto run.
3. Dispatch via the eLogii driver app. The route lands on the driver’s phone in the eLogii app for navigation, POD, photos, signatures and custom forms.
4. Write back to the order system. Completion data, POD references and timestamps write back to the upstream order system for invoicing and inventory.
5. FourKites continues unchanged. Multi-carrier visibility, predictive ETAs and yard / dock surfaces keep running on the FourKites side. eLogii does not write into FourKites.

Most teams complete the integration in 3 to 5 weeks. Typical first wave: one depot, one region or one business unit. Validate on real historical orders, then expand.

Frequently asked questions

Does FourKites have built-in route optimization?

No. FourKites is a multi-modal in-transit visibility platform for shipments moving across carriers. It has no constraint-aware multi-stop route optimization engine for own-fleet operations. Customers running their own delivery fleet alongside contracted carriers typically add a routing layer for own-fleet operations alongside FourKites.

What do FourKites users typically do for own-fleet routing today without an optimizer?

Three common patterns: spreadsheets and manual planning (planner lays out stops by hand each morning), a basic stop sequencer (orders the stops once vehicles are pre-assigned but does not optimize against time windows or capacity), or an external routing tool with manual order copy-paste. None scale cleanly past 50+ in the field, multi-depot, or recurring patterns.

How does eLogii integrate with FourKites for routing?

Not directly. eLogii integrates with your order system (ERP, TMS or OMS), reads orders from there, optimizes and dispatches the eLogii driver app, and writes completion back to the order system. FourKites continues to capture multi-carrier visibility on its side. Optionally, eLogii can read FourKites’ predictive ETAs on inbound carrier shipments to phase outbound own-fleet plans; eLogii does not write into FourKites.

What route optimization constraints does eLogii model?

Vehicle capacity (weight, volume, pallet count), time windows (per customer and per stop), driver skills, shift hours, depot start and end, SLA windows, customer-confirmed slots, multi-day routes, multi-depot routes, return-to-depot rules, recurring service patterns. Two engines: Default for high-throughput single-day planning (100 tasks in under 10 seconds), Advanced for multi-depot, multi-day, constraint-heavy work. Six modes: three assignment plus three load-balancing.

Does adding eLogii change anything in FourKites?

No. FourKites continues to capture multi-carrier visibility on its side of the stack. eLogii adds the routing and field-execution layer for own-fleet operations on the other side, connecting to the order system in the middle.