Demand forecasting
Forecast demand to plan inventory and capacity.
AI for supply chain & logistics
AI that moves with your operation.
Logistics AI has to hold up against real-world disruption. We build demand, routing and inventory systems with the monitoring and resilience operations teams rely on.
SECTOR HIGHLIGHT
Routing
Optimization and financing tools for freight, inventory, routing, and disruption response.
See logistics casesThe sector challenge
In logistics, the plan is only as good as it survives reality.
Disruption is the norm, not the exception. We build models that stay useful when conditions change.
CHALLENGE
Real-world disruption
Weather, demand spikes and delays break brittle plans.
CHALLENGE
Fragmented data
Data sits across systems and partners and has to be unified.
CHALLENGE
Real-time decisions
Routing and allocation decisions happen continuously.
CHALLENGE
Cost and carbon
Optimizing cost and emissions together is a hard tradeoff.
What we build
Systems across the supply chain.
Route and fleet optimization
Optimize routing, loads and fleet utilization.
Inventory intelligence
Right-size stock across the network and reduce waste.
Warehouse automation
Computer vision for sorting, counting and quality.
Disruption prediction
Anticipate delays and risks before they cascade.
Carbon analytics
Measure and cut the footprint of moving goods.
Supply chain case studies
All
Sustainability · Carbon ReductionReducing Supply-Chain Emissions by 10% and Saving $5M
Applied AI across logistics planning to cut emissions and operating costs in enterprise supply chains.
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Route Optimization · CarrytReducing Delivery Distance, Fuel Use, and Emissions by 15%
Machine learning and graph theory optimized delivery routes while lowering fuel use and emissions.
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Last-Mile DeliveryReducing Last-Mile Delivery Times by 10%
AI-enhanced route optimization for faster and more reliable last-mile delivery operations.
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Urban Mobility · ForecastingPredicting Traffic Congestion for Smarter Urban Mobility
Short-term congestion prediction using machine learning for better logistics and city planning.
Read case studyWhat is AI in supply chain?
AI in supply chain refers to the use of artificial intelligence technologies like machine learning, predictive analytics, optimization algorithms, computer vision, and intelligent automation to improve logistics operations, inventory management, transportation planning, supply chain visibility, and operational decision-making.
How is AI used in supply chain management?
AI is used in supply chain management for route optimization, inventory forecasting, shipment visibility, logistics automation, supplier coordination, demand prediction, disruption monitoring, and transportation intelligence.
What are examples of AI supply chain solutions?
Examples include AI-powered route optimization systems, supply chain visibility platforms, demand forecasting models, inventory optimization systems, cargo inspection AI, AI agents for logistics operations, and predictive transportation analytics.
Can AI improve supply chain visibility?
Yes. AI-powered supply chain visibility solutions help organizations monitor shipments, predict delays, identify operational bottlenecks, and improve transparency across transportation and logistics networks.
What are AI agents in supply chain operations?
AI agents in supply chain operations automate workflows, analyze operational data, support logistics planning, generate recommendations, and improve decision-making across supply chain environments.
Does Omdena build custom AI solutions for supply chain and logistics?
Yes. Omdena develops custom AI-powered supply chain management solutions tailored to logistics providers, manufacturers, pharmaceutical companies, transportation operators, retailers, and enterprise supply chain teams.
Optimizing a supply chain with AI? Let's ship it.
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