Optimisation recommendations are reviewed and approved by dispatchers.
AI & Logistics case study
AI-assisted load planning that keeps dispatchers in control of legally sensitive decisions.
A European freight operator needed one operational view across hubs, dispatchers, vehicles, loads, drivers, customers, and finance. The business also needed a practical way to consolidate freight from multiple orders without exceeding trailer floor capacity, legal vehicle weight, or permitted drive-axle limits. Eleco Technologies delivered a responsive Transport Management System and an AI optimisation engine that translates these operational constraints into clear recommendations for dispatcher approval.
AI-assistedLoad planning
Recommendations for dispatcher approval
3Core physical constraints
Floor capacity, legal weight, axle load
End-to-endOperational view
From hubs to finance
Dispatcher-ledDecision control
Human approval remains essential
Trailer floor metres, legal total vehicle weight, and drive-axle load are evaluated together.
Hubs, dispatchers, vehicles, loads, drivers, customers, and finance are connected in one platform.
Client challenge
What the organisation needed to solve
Freight planning depended on reconciling multiple operational variables at once: destination, delivery sequence, available trailer floor metres, shipment weight, total legal vehicle weight, drive-axle limits, vehicle availability, and customer commitments. Without a single operational view, dispatchers had to coordinate information across hubs, drivers, loads, customers, and finance while making legally sensitive consolidation decisions under time pressure. The operator needed an approach that improved planning quality without replacing the human judgement required for safety, compliance, and customer service.
Eleco Technologies solution
How the platform addressed the problem
Eleco Technologies built a responsive Transport Management System and an AI optimisation engine for the back office. The engine evaluates destination, delivery sequence, route efficiency, shipment weight, available trailer floor metres, total legal weight, and maximum permitted drive-axle load. It then recommends load consolidation and delivery routes, presenting those recommendations to dispatchers for approval. The platform brings fleet tracking, driver compliance, customer operations, and financial reporting into the same operational environment so planning decisions are supported by a complete view of the business.
Delivery model
Structured engineering delivery with clear team, timeline, and stack evidence.
Team composition
Logistics workflow specialists
Transport platform engineers
AI optimisation engineers
Dispatcher and operations stakeholders
Delivery approach
Structured the platform around a shared operating picture spanning hubs, dispatchers, vehicles, loads, drivers, customers, and finance rather than a standalone route-planning tool.
Translated physical and legal transport constraints into explicit optimisation inputs, including trailer floor capacity, total permitted vehicle mass, and drive-axle limits.
Kept dispatchers in the decision loop: the AI engine recommends feasible load combinations and delivery routes, while operational teams retain responsibility for approval.
Technology stack
Responsive Transport Management SystemAI optimisation engineLoad consolidation workflowRoute optimisationFleet trackingDriver complianceFinancial reporting
Measured outcomes
Operational results that make the engagement commercially credible.
Supports better truck utilisation by identifying feasible consolidation opportunities across multiple freight orders and operational constraints.
Accelerates planning by bringing destination, route, shipment, capacity, vehicle, driver, customer, and finance context into one operational view.
Reduces avoidable kilometres through route recommendations that account for delivery sequence and route efficiency.
Maintains dispatcher oversight for legally sensitive decisions involving vehicle weight, axle load, and operational feasibility.
"The objective was not to automate away dispatcher judgement. It was to give dispatchers a stronger operational view and practical recommendations they could validate against real-world transport constraints."
— Eleco Technologies delivery team
Evidence points
What the delivered system included
AI load consolidation recommendations for freight originating from multiple orders
Route optimisation that evaluates destination, sequence, and route efficiency
Operational protection against trailer floor, legal weight, and drive-axle limit breaches
Transport management workflows for fleet tracking, driver compliance, customers, and financial reporting
Engineering Delivery Review
Turn evidence from similar work into a practical delivery plan.
If your organisation is planning a platform build, modernisation, internal workflow system, or AI-ready automation layer, Eleco Technologies can review the opportunity, risks, team model, and first delivery phase.