Early accessRoute optimization & dispatch for delivery fleets
Delivery routes that adapt when the day doesn’t go to plan.
LogiRoute AI plans multi-stop routes around delivery windows, vehicle capacity and real travel times. During the day it flags stops at risk of running late and proposes re-dispatch moves your dispatchers approve in one click.
Routes respect delivery windows, vehicle capacity, driver shifts and depot cut-offs, not just distance.
Re-dispatch with a human in the loop
When traffic or a failed attempt puts stops at risk, the platform proposes moves. Dispatchers approve or reject them.
Built for imperfect addresses
Landmark-based and incomplete addresses are flagged and scored before routes are built, so drivers aren't left guessing.
Maintenance signals from route load
Vehicle health is read alongside how hard each vehicle is being driven, so service can be booked before a breakdown.
The problem
Most delivery fleets are still dispatched from spreadsheets and phone calls.
Fleets that run 20 to 200 vehicles often plan routes by hand, then spend the day reacting. Each disruption is handled in isolation, so small delays turn into missed windows, repeat trips and overtime.
01
Routes are built by hand at 6 a.m.
Dispatchers combine order exports, spreadsheets and map tabs to assign hundreds of stops. The plan depends on whoever builds it, and it takes the first hour of the shift.
02
The plan breaks by 10 a.m.
A blocked road, a late loading bay or an unreachable customer cascades into missed windows. Re-planning happens over phone calls and chat groups with no view of the whole fleet.
03
Failed deliveries are paid for twice
Every missed window or wrong address means another trip: more fuel, more driver hours, another call from an unhappy customer and less capacity for tomorrow's orders.
04
Growth means more dispatchers, not better routes
Manual planning scales linearly. Add 20 vehicles and you add planning hours, overlapping routes and blind spots that no one has time to analyse.
Generated in minutes from the day's orders and constraints
When traffic hits
Phone calls and chat groups, one driver at a time
At-risk stops flagged with ranked re-dispatch options
Bad addresses
Discovered by the driver at the door
Scored and flagged before the route is dispatched
Vehicle faults
Found when a loaded vehicle breaks down
Signalled early from health data and route load
Performance view
End-of-month spreadsheet reconciliation
On-time rate, km per stop and failure reasons by route
Core features
Six capabilities, one dispatch workflow.
Each feature handles one stage of a delivery day, from building the plan before dawn to explaining what happened after the last drop.
Sample data
01
Multi-stop route optimization
Generates daily routes across your fleet from the day's orders, balancing stops per vehicle against time windows, payload and volume limits, shift lengths and depot departure times.
Why it matters: Fewer kilometres per drop and a plan that holds up, produced in minutes instead of a morning.
Feeds the dispatch board and driver route sheets.
Plan comparison · 98 stops
Optimized
Time windowsPayload ≤ 1.5tShift ≤ 9hDepot out 07:30Bridge access
Metric
Manual plan
LogiRoute plan
Vehicles used
6
5
Planned distance
312 km
234 km
Stops outside window
11
2
Longest shift
10h 40m
8h 55m
02
Live re-dispatch suggestions
Monitors driver progress against the plan. When a stop is projected to miss its window, it proposes concrete moves: resequence, reassign to a nearby vehicle, or reschedule.
Why it matters: Dispatchers decide in seconds with the trade-offs in front of them, instead of rebuilding routes by phone.
Approved moves update driver routes and the activity log.
Re-dispatch queue · 3 open
Resequence R-102
Window closes 11:00 · conf. 0.91
Reassign 3 stops → R-103
Congestion +35 min · conf. 0.84
Hold SHP-24830
Address score 41 · conf. 0.77
03
Delivery zone clustering
Groups dense delivery drops into balanced zones using location, order volume and access constraints such as bridges, one-way corridors and gated estates.
Why it matters: Less route overlap between drivers and zones that new drivers can learn quickly.
Zones become the starting point for each day's optimization.
Zones · Lekki Hub
5 zones · 125 drops
04
Delivery window risk & ETAs
Predicts arrival times from historical trip data, time of day and stop service times, and scores every stop's risk of missing its window throughout the day.
Why it matters: Customer service knows about a late delivery before the customer calls.
Risk scores trigger re-dispatch suggestions and customer notices.
ETA vs window · live
On timeAt riskLate
10:14
R-101
R-102
R-104
R-105
08:0010:0012:0014:0016:00
05
Predictive maintenance signals
Combines vehicle health inputs with route intensity, such as stop density, idle time and distance, to surface vehicles trending towards a fault.
Why it matters: Service is booked between shifts, not after a breakdown strands a loaded vehicle.
Flagged vehicles are held back from long routes during planning.
Fleet health × route load
AAA-118Brake wear trend
61
LND-730Coolant temp on idle
74
KJA-412No anomalies
88
06
Proof of delivery & cost analytics
Captures delivery outcomes, photos and exceptions per stop, then rolls them into on-time rate, kilometres per stop, failed-attempt reasons and cost per drop by route, depot and customer.
Why it matters: A shared, factual view of fleet performance for operations, finance and key accounts.
Run a dispatch morning in the LogiRoute AI workspace.
This is a working demo of the dispatcher workspace, loaded with a fictional courier fleet across three depots. Every control responds, and nothing is sent anywhere.
Try this
→Open the dispatch queue and approve or reject a re-dispatch suggestion
→Filter shipments by “At risk” or search for “Lekki”, then open a record
→Book a service for a vehicle flagged in Fleet health
→Switch analytics between on-time rate, km per stop and failed attempts
Kestrel Parcel Co.
Wednesday · Wave 1
Sample data
Today's operations
Wave 1 · dispatched 07:58
Stops in wave
98
46 completed
Completion
47%
5 routes active
At risk / failed
4 / 1
Review dispatch queue
Planned distance
234 km
Across all routes
Live routes
AI insight
Move 3 stops from R-105 to R-103
Congestion on Lekki–Epe Expressway at Abraham Adesanya is adding ~35 min to R-105. R-103 has capacity and passes within 1.2 km.
Activity
10:14R-105 projected 35 min behind plan after congestion at Abraham Adesanya.
09:52Maintenance signal raised for Truck AAA-118 (brake wear).
09:40SHP-24826 delivered at Harbourview Offices. Photo POD captured.
07:58Wave 1 dispatched: 5 routes, 98 stops.
Sample data. Kestrel Parcel Co., its drivers, customers and figures are fictional and do not represent LogiRoute AI customers or results.
Who it's for
Built for fleets where the delivery window is the product.
LogiRoute AI is designed for operators running roughly 10 to 500 vehicles from one or more depots, with dispatchers who own the day's plan.
Courier & parcel delivery
Last-mile courier companies and 3PLs running vans and motorbikes across dense urban areas.
The problem
Hundreds of small parcels a day with tight windows, frequent failed first attempts and heavy traffic variance.
How they use LogiRoute AI
Zone clustering for daily waves, optimized multi-drop routes per rider, and re-dispatch when a rider falls behind.
The benefit
More successful first attempts and fewer riders crossing each other's zones.
FMCG & beverage distribution
Distributors delivering to retailers, supermarkets and wholesale outlets from regional depots.
The problem
Mixed vehicle types, pallet and weight limits, outlet receiving hours and long multi-stop runs.
How they use LogiRoute AI
Capacity-aware routing by payload and volume, outlet receiving windows, and maintenance signals for trucks on heavy routes.
The benefit
Fuller vehicles, fewer partial-load return trips and trucks kept off the road before they fail.
E-commerce & retail fulfillment
Online retailers and fulfillment teams that run their own delivery fleet or manage delivery partners.
The problem
Order volume swings by day and campaign, and customers expect accurate ETAs and proactive updates.
How they use LogiRoute AI
Daily optimization from order exports, window risk scoring and delivery outcome analytics by area.
The benefit
Reliable delivery promises at checkout and a clear view of where delivery cost is going.
Pharmaceutical & medical supply
Distributors supplying pharmacies, clinics and hospitals with time-sensitive stock.
The problem
Priority orders, strict receiving times and the need for verifiable proof of delivery.
How they use LogiRoute AI
Priority-weighted routing, re-dispatch for urgent orders and photo and signature proof of delivery per stop.
The benefit
Urgent orders protected in the plan and a delivery record that answers disputes quickly.
Technology
How We Use Amazon Web Services
LogiRoute AI’s architecture is designed on AWS around the shape of a delivery day. Orders and GPS events stream in, spatial data is stored and geocoded, prediction models and the routing solver turn it into plans, and dispatchers act on the results in a secure web workspace. Each stage below maps a product capability to the AWS services that carry it.
Stage 1
Data Collection
Amazon API Gateway
Amazon Kinesis Data Streams
Order imports, fleet updates and driver GPS pings enter through authenticated APIs and a telemetry stream.
Stage 2
Secure Storage
Amazon RDS for PostgreSQL
Amazon S3
Orders, stops, routes and geometry live in PostgreSQL with PostGIS. Raw telemetry, imports and proof-of-delivery photos go to S3.
Stage 3
Processing
AWS Lambda
Amazon Location Service
Event-driven functions validate orders and geocode addresses, then build the travel-time matrices the optimizer needs.
Stage 4
AI Intelligence
Amazon SageMaker AI
Amazon EC2
Models predict travel times, window risk and maintenance signals. Solver workers compute and re-compute routes.
Stage 5
Application Experience
Amazon Cognito
Amazon CloudWatch
Dispatchers and drivers sign in to role-scoped workspaces. Pipeline health, latency and model jobs are monitored centrally.
AWS services in the LogiRoute AI architecture
Amazon API Gateway: Exposes the REST endpoints for order import, fleet management and driver app check-ins, with throttling and request validation.
Amazon Kinesis Data Streams: Ingests continuous driver GPS and stop-status events so route progress can be compared with the plan in near real time.
Amazon RDS for PostgreSQL: Stores orders, stops, vehicles, routes and delivery zones, using the PostGIS extension for spatial queries and zone geometry.
Amazon S3: Holds uploaded order files, archived trip telemetry for model training, and proof-of-delivery photos and signatures.
AWS Lambda: Runs event-driven tasks: order validation, address quality scoring, ETA refresh triggers and notification hand-offs.
Amazon Location Service: Provides geocoding for delivery addresses and road-network route matrices used as optimizer inputs.
Amazon SageMaker AI: Trains and hosts the travel-time, delivery-window risk and predictive maintenance models on historical trip data.
Amazon EC2: Runs the compute-intensive vehicle routing solver workers that generate daily plans and re-dispatch options.
Amazon Cognito: Manages sign-in and role-based access for operations managers, dispatchers and drivers in each customer workspace.
Amazon CloudWatch: Collects logs, metrics and alarms across ingestion, optimization jobs and APIs so failures are caught before dispatch.
Early access
Bring us a week of your deliveries.
LogiRoute AI was founded in 2026 and is building its platform with delivery operators through an early-access program. If your team plans routes by hand or spends the day re-planning, we want to hear how you work.
1
Intro call
We learn how your fleet is dispatched today: depots, vehicle mix, order volumes and where the day usually breaks.
2
Data review
You share a representative sample of past orders. We use it to configure constraints and show what an optimized plan looks like for your operation.
3
Early-access setup
Selected operators get access to the workspace and work directly with the founding team on configuration and feedback.
Founded
2026
Stage
Building
Model
B2B SaaS
Pricing
Subscription plans sized to your fleet.
Plans scale with fleet size and the capabilities you need. Pricing is agreed with each early-access customer based on vehicle count, depots and integration scope.
A founding team covering product and customers, engineering and architecture, and finance.
AR
Abdulrazaq Rotimi
Chief Executive Officer
Leads LogiRoute AI's strategy, customer development and partnerships, working with delivery operators to shape the product around how fleets are dispatched day to day.
PT
Patriarch Tongo
Chief Technology Officer
Leads engineering and the platform architecture, from route optimization and prediction models to the cloud infrastructure the product runs on.