Graph neural networks for routing, quantile models for demand, telemetry models for maintenance, and vision for warehouses — all trained in PyTorch on NVIDIA GPUs, and fitted to your own operating data rather than a generic benchmark.
Makzom is built on a modern AI-powered technology stack designed to process operational data in real time, automate complex workflows, and deliver predictive insights that improve logistics performance.
Our platform integrates advanced AI models, real-time analytics, cloud infrastructure, and intelligent automation into one scalable ecosystem — the technology foundation for modern logistics across fleets, warehouses, and supply chains.
Four model families, one per logistics problem.
GPS, sensor and scan events processed as they arrive.
PyTorch with mixed-precision on NVIDIA hardware.
Every output carries expected impact and confidence.
Makzom trains its own models rather than wrapping a general-purpose API. Each problem in logistics has a different structure, so each gets an architecture suited to it.
Graph neural networks + constrained routing solver
Graph neural networks over road-network topology learn edge-level travel cost from historical trip and traffic data. A vehicle-routing solver consumes those learned costs to generate multi-stop routes under capacity, time-window and driver-hour constraints.
Temporal sequence models with quantile regression
Sequence models trained on historical shipment volume, seasonality and external demand signals produce probabilistic forecasts. Quantile outputs give capacity and inventory decisions explicit confidence intervals rather than a single point estimate.
Temporal convolutional & recurrent models on telemetry
Models over vehicle telemetry streams — engine, brake, tyre and fuel sensors — score component degradation and estimate remaining useful life, surfacing likely failures before they become roadside breakdowns.
Fine-tuned detection & segmentation backbones
Detection and segmentation backbones fine-tuned on warehouse and yard imagery handle pallet and label recognition, load verification and damage detection from standard camera feeds.
Makzom uses a cloud-native architecture that securely processes large volumes of logistics data while maintaining high availability and performance.
Cloud-native by design
Secure, scalable, and always available.
A connector layer normalizes data from the systems you already run, so models train on your history without a rip-and-replace migration.
Models train on your data to serve your network — never pooled into a shared model sold to anyone else. Encrypted in transit and at rest, with access scoped per role.
Makzom combines advanced AI technologies with enterprise-grade infrastructure to help businesses modernize logistics operations and scale with confidence.
Enterprise-grade AI infrastructure
Built to scale securely with your operations.
Makzom helps businesses leverage AI and intelligent automation to improve operational efficiency and drive sustainable growth.
Average efficiency gain
+62%
Discover how Makzom’s AI-powered technology platform can help your business optimize logistics operations, automate workflows, and achieve greater operational efficiency.
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