AI for Logistics

AI powered applications can help the logistics industry to scale their ML models, lower operational costs and drive accountability and transparency in their processes.

With the Katonic MLOps platform, data science teams enjoy the power of a unified AI orchestration platform to manage their entire AI lifecycle in one place, making things easier, faster and more efficient.

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7x

More cost-effective infrastructure

Reduction in computing costs through efficient management of data science work loads.

12x

Faster deployments

Faster and a more reliable way to deploy and improve models in production

85%

Reduction in manual labour costs

Reduction in manual labour costs resulting from higher productivity of data science teams

How can AI help?

AI can help logistics industry to achieve,

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Optimal utilization of ship's capacity through computer-vision-fueled positioning system.

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Increased safety using predictive maintenance and automated responses.

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Planning shipment of containers through predictive scheduling.

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Streamlining backoffice and warehouse operations.

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Route planning, forecasting, and optimization.

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Dynamic pricing for the freight industry.

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Demand predictions.

Which in turn leads to,

Businesses implementing AI have achieved

Reduction in logistics cost by 15%

Decrease in inventory levels by 35%

Increase in service levels by 65%

Build power AI applications with the Katonic MLOps platform

With the award-winning Katonic MLOps platform, your data science team can build powerful AI applications. Some of the ready-to-try models available on the Katonic platform are,

Late shipment prediction

Predict late shipments in a supply chain network so that businesses can prepare for foreseeable delays and take data-driven corrective action.

Supplier base optimisation

Enhance your view of suppliers and pre-emptively design a Supplier Management Strategy.

Inventory forecasting

Predict inventory utilisation for 30 months in advance using historical monthly Inventory data.

Product demand forecasting

Forecast 36 months of product demand using historical monthly demand data.

Part shortage prediction

Predict part shortages in a supply chain network so that businesses can prepare for foreseeable delays and take data-driven corrective action.

The Katonic advantage

The Katonic MLOps platform allows enterprises to manage their entire AI lifecycle needs on a single platform rather than relying on multiple tools and platforms, saving time and effort. Enterprises use the platform for experimenting, deploying, monitoring, and managing ML models all in one place, facilitating collaboration between data scientists, engineers, and other stakeholders throughout the ML model development and deployment process, ensuring that everyone is working towards a shared goal and minimising silos of information.

Born in Kubernetes, the platform is cloud-agnostic, meaning customers can deploy ML workloads on any cloud environment (i.e. on-premises/private cloud or any public cloud) allowing Katonic to run natively in any cloud or on-premises environment with the full benefits of elastic scaling of heterogeneous data science workloads.

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