The ever-changing retail landscape is a constant challenge for stocking the right amount of inventory in your DCs. Rubikloud’s AI Engine continuously analyzes all data sources, including retailer POS, inventory, shipment, promotion, market, competitive and external data, to produce forecasts that more accurately align to actual SKU-level consumption.
%
INCREASE IN FORECAST ACCURACY
Client saw a 33% improvement in forecast accuracy compared to their currently established method.
Unlike other enterprise solutions, Rubikloud’s AI Engine integrates directly into your existing legacy applications minimizing the potential disruption from change management. With outputs that funnel right back into your demand planning workflows and technologies, teams can align on and implement plans faster.
Other forecasting solutions use methods that are static, unadaptable, and do not improve over time.
Based on your organization’s goals and objectives, Rubikloud’s ML models continually learn from your data in real-time to produce constantly improving forecasts that reflect actual demand.
Our expandable solutions ingest data from all your raw sources and quickly converts it into a clean, usable data model. This removes the onus from internal resources and allows for seamless integration back into your legacy systems.
Our proven solutions are deployment ready, no need for costly custom builds or lengthy sessions that never lead to anything tangible. This approach delivers the fastest time to value on the market while optimizing total cost of ownership.
Using our best-in-class, industry specific Machine Learning expertise, we tackle the most complex and nuanced business challenges uniquely impacting retailers.