Retail Copilots

Predictive and generative AI addressing retail’s biggest challenges

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Unlock retail innovation and productivity with generative AI

Early adopters are already seeing competitive advantages, enhanced productivity, and improved customer intimacy

Tap the power of predictive and generative AI together like never before. Understand what’s happened and plan for what’s next with smart copilot interfaces tailored for retail. The Category Manager Copilot intelligently integrates with CINDE Intelligence and Insights Builder, while the Demand Planner Copilot works seamlessly with DFAI. Both combine predictive and descriptive models for valuable historical insights and future predictions.

Designed for merchandising executives and category managers, the Category Manager Copilot thinks like a category manager providing guidance and insight to optimize performance and drive profitable growth through real-time predictive analytics. The copilot uses generative AI to query datasets and then collate information into one unified view via a holistic, easily understood, natural language narrative.

The Demand Planner Copilot puts the power of a half dozen MBAs at the disposal of any demand planner or replenisher. It automatically queries the predictive models and data sets to solve day-to-day problems faster and address otherwise untouched challenges to deliver better forecast accuracy and provide more time back in your day.

Unlock new insights and prescriptive analytics with generative AI copilots

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Decisions at scale

Analyze large volumes of data to uncover patterns, trends, and deliver impactful insights in real-time.

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Accelerated growth

Proactively discover previously uncovered opportunities to drive growth.

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Transformative user experience

Intuitive and easy-to-use natural language interface that ties predictive solutions with generative AI.

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Elegant user experience

Clear, consistent, and logical designs deliver unparalleled experience and simplified workflows.

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Intelligent assistant

Proactively asks “what if” questions to make better informed decisions and uncover growth opportunities.

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Retail-specific Large Language Model (LLM)

Fine-tuned for the retail industry and optimized to deliver knowledge graphs and contextualization.

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Private and secure

User-identified access control enhances security.

Next-gen predictive and generative Eureka AI architecture

Woman with blonde hair tied in a bun shopping in a grocery store refrigerated aisle, reaching for an item on the shelf while holding a shopping basket containing vegetables.Smiling woman wearing a red beanie and beige coat holding a blue product box in one hand and using a smartphone with the other in a store aisle filled with various products.A woman in a gray blazer with black sleeves stands in a large warehouse aisle surrounded by tall shelves full of boxes, holding and interacting with a tablet.Two women sitting at a desk in a warehouse, focused on a laptop screen with documents in hand, surrounded by shelves with packed boxes.
Store and Space
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Real-time visibility, flawless execution

Merchandising and Marketing
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Complex insights, recommendations at scale

Supply Chain
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Superior shopper experiences, lower costs

Data Collaboration and Monetization
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Improve data use and monetization