Stockouts and on-shelf-availability is a $984 Billion problem globally for consumer goods manufacturers. Ensure the optimal inventory levels at all times and adapt to changing factors and external shocks with AI powered order fulfillment and auto-replenishment
at the store or DC level. DeepVu's Order Fulfillment VuDecide decision models recommend the DC to fill from, the quantity, split order or not, and shipping method in order to optimize fulfillment KPIs (typically freight cost, delivery date, split-order penalty and OTIF penalty). For B2B customers, our models can also decide the TruckLoad build as well, and the shipping date.
These Generative AI decision models (VuDecide) learn from your historical inventory levels, purchase orders (whether ecommerce, or B2B), the historical fulfillment decisions, sales promotions and logistics data augmented with DeepVu's real-time Knowledge Graph platform aggregating numerous external micro and macro economic signals to accurately forecast future demand. New actual sales records coming in are used to continuously self-tune and improve the accuracy of VuDecide Generative AI decision models. Furthermore, DeepVu's models can also optimize OTIF score per retail customers DC/store per SKU per month.
Minimize inventory holding costs while meeting customer demand with Auto-replenishment decision models
Optimize order fulfilment to honor promised delivery date and minimze freight costs
Optimize Aging and minimize frequency of forced promotions and liquidation while smartly redeploying lots to DCs with higher demand while optimizng freight cost
Optimize your OTIF scores and avoid penalties
Move faster and save time by always having relevant, real-time intelligence for decision making.
Deep learning continuously improves over time and dynamically adapts to your growing business.
AI automates processes and analytics enabling you to focus on customer satisfaction.