Analyze thousands of multi-layered patterns found in breakdowns and process-led production losses to identify high-risk components and recommend prescriptive action.
Provide consumer-focused manufacturing by identifying subtle and granular demand patterns at SKU and POS levels.
Rapidly analyze data from a variety of sources, including internal enterprise applications, sensor networks, operational systems, and exogenous third-party data to power actionable insights.
Compute part-level demand forecasts based on production orders and assemblies, traversing multi-level, time-varying BOM files.
Analyze enormous volumes of various data to forecast demand, supply, quality issues, and market trends.
Analyze operational management — supply chain, logistics, field — and determine new factors that affect performance.
Accurately forecast equipment failures, and recommend action before faults and breakdowns cause costly delays.
New world, new models….Data and AI have the opportunity to drive more impact than ever
A global mining company wanted to optimize operational costs by reducing fuel consumption for each vehicle across its fleet.
Nearly all existing models have been invalidated by the coronavirus pandemic. They will presumably be invalidated again as the situation evolves as the world recovers. Even after recovery, it is unlikely that we will return to where we started before the crisis began. So how does that affect our data models?
AI analytics helps major banks stay connected to their customers – especially during the dramatic rise of online financial management use. As leading banks apply a range of strategies to navigate the new normal, AI analytics is opening greenfield opportunities to raise profits, combined with agility and ethical responsibility.