Route optimization alongside Motive

What Motive ships today around the vehicle and the driver

Motive is comprehensive on the telematics, compliance and safety side, and several of its modules touch the delivery problem at the edge. Drawing the line precisely matters when scoping a routing layer alongside it.

• Vehicle Gateway and dashcam. Hardware on the vehicle streams GPS, engine data, fuel, idling, harsh-event detection and forward / driver-facing video to Motive’s cloud.
• Motive Driver app. Driver-side mobile app on iOS and Android: ELD / HOS logging, DVIR pre-trip and post-trip inspections, dispatcher messaging, fuel-card prompts, dashcam event review. Compliance and safety surface, not a delivery POD or stop-execution surface.
• Fleet Dashboard and live map. Internal-facing fleet ops view: where every vehicle is right now, geofence alerts, exception rules, driver safety scores. No optimized stop list, no end-customer ETA.
• Spend management and maintenance. Motive Card, fuel-spend tracking, scheduled maintenance and inspection records. Operationally important; not routing-side.
• Fleet API and webhooks. Programmatic access to vehicles, drivers, locations, DVIR, HOS, fuel and safety events for integration into ERPs, TMSs and routing platforms.

Motive was not built to be a routing engine, and the modules above are the right tools for what they cover. Where Motive stops is the route plan itself, the order each stop runs in, and the constraint set the 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 Motive is designed to do. It is a separate workload that needs its own engine.

Where Motive users land today without a routing layer

Three patterns are common in Motive 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 Motive. 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 reads vehicles and drivers from Motive directly, plans against real constraints and sends the plan back as context for dispatchers. That is the role eLogii plays.

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 maps to a vehicle’s home base in Motive.
• 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 with Motive

The combined deployment leaves Motive in place as the telematics system of record. The integration runs over both products’ REST APIs.

1. Read from both sides. eLogii pulls open delivery orders from the upstream order system on one side and reads vehicles, drivers, locations and HOS from Motive’s Fleet API on the other. 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. The Motive Driver app continues to run alongside for HOS, DVIR and dashcam.
4. Write back. Completion data, POD references and timestamps write back to the upstream order system for invoicing and inventory. Optionally, the assigned vehicle and stop list can be sent to Motive so dispatchers see route context next to live telematics.

Most teams complete the integration in 3 to 5 weeks. Typical first wave: one depot, one region or one business unit (often the route the planner spends most time on by hand). Validate on real historical orders, then expand.

Frequently asked questions

Does Motive have built-in route optimization?

No. Motive is a fleet telematics, compliance and driver-safety platform: GPS, engine data, DVIR, HOS, AI dashcam, fuel cards. It has no constraint-aware multi-stop route optimization engine. Customers running own delivery fleets or field-service teams typically add a routing layer alongside Motive.

What do Motive users typically do for 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 Motive for routing?

Through both products’ REST APIs. eLogii pulls open delivery orders from the upstream order system and reads vehicles, drivers, locations and HOS from Motive’s Fleet API. The optimizer runs in eLogii against vehicles, depots, capacities, time windows, skills and SLAs. The day’s assigned vehicle and stop list can be sent back to Motive so dispatchers see route context next to live telematics; completion data writes back to the upstream order system for invoicing.

What route optimization constraints does eLogii model?

Vehicle capacity (weight, volume, pallet count), time windows (per customer and per stop), driver skills, shift hours, HOS remaining, 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 Motive?

No. Motive continues to own telematics, HOS, DVIR, dashcam, fuel and driver safety. eLogii adds the routing and field-execution layer on top: optimized routes, the on-road driver app, live ETAs, branded customer tracking and POD. The Motive Driver app and the eLogii driver app run side by side on the same phone.