AI Sommelier for Immersive In-Store Experience

Overview

The project aimed to create a next-generation digital sommelier that transformed in-store retail experience. The AI-powered assistant was designed to help customers explore and select alcoholic beverages with confidence and ease.

The system provides a personalized and educational shopping experience, combining professional expertise, sensory storytelling and real-time product discovery. Deployed as part of an ecosystem, it includes an in-store kiosk-based interface with a dedicated branded design, as well as integration into the retailer’s native mobile app offering extended functionality such as pre-ordering and home delivery. During the in-store visit the assistant guides customers from product exploration to purchase enhancing satisfaction, engagement and sales conversion.

 Key business objectives included:

• Deliver expert-level guidance and enhance store experience for every customer, regardless of staff availability, time of day or level of product-specific knowledge.
• Offer dynamic recommendations based on customer preferences, taste profiles or natural-language queries (e.g. “light-bodied red wine,” “smoky scotch,” “something bubbly like prosecco”).
• Improve store navigation and reduce decision fatigue to help customers quickly locate items through digital maps and route visualization.
• Boost cross-selling and discovery by introducing customers to new products, pairings and brands, increasing the average basket size and engagement time.
• Reduce reliance on in-store consultants and ensure consistent communication standards across all locations.

The Challenges

Before implementation, customer interactions in beverage retail were often fragmented and dependent on human staff and customer’s own product knowledge, creating inconsistent customer experiences.

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• Limited accessibility to expertise. During peak hours or in smaller stores customers often lacked timely access to qualified consultants, leading to missed opportunities for education and upselling.
• Complex product assortment. Large selections of wines, spirits and craft beverages overwhelmed customers unfamiliar with the nuances of regions, varieties or production methods.
• Static digital tools. Existing digital aids (mobile apps and search terminals) were limited to price lookup or inventory availability, offering no guidance, personalization or storytelling.
• Inconsistent recommendations. Human consultants varied in expertise, knowledge and tone resulting in uneven quality of advice and diluted brand identity.
• Navigation friction. Customers struggled to find specific items or understand shelf organization, reducing overall satisfaction and purchase conversion.

As a result, shopping experience frequently became confusing and difficult due to limited guidance and lack of personalized recommendations, making the selection process tedious.

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Our Solution

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To address these challenges, we built an AI-driven in-store sommelier – a conversational multimodal assistant capable of recognizing products, understanding taste preferences and guiding customers through the store.

The assistant merges LLM-powered dialogue, computer vision and real-time navigation to deliver a seamless retail journey that feels human yet operates with the precision and scalability of AI.

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Key Capabilities include:

• Sommelier Expertise. Trained on an extensive beverage knowledge base encompassing wines, spirits and breweries, the assistant engages customers in natural dialogue offering pairing advice, tasting notes and contextual insights comparable to a professional sommelier.
• Label Recognition. Using computer vision, customers can scan a bottle label to instantly receive product details such as producer background, origin, vintage, flavor profile, awards and user reviews.
• Personalized Recommendations. Through natural-language understanding, the AI interprets open-ended queries and curates selections tailored to user intent, budget and flavor preferences. Similarity-based recommendations encourage exploration of new or premium options.
• Interactive Store Navigation. Integrated with store planograms, the assistant can visually display or describe the exact route to a selected bottle or category reducing search time.
• Cross-Selling and Pairing Suggestions. The assistant recommends complementary products such as snacks, mixers or accessories and promotes discovery across adjacent categories increasing average order value.
• Analytics and Insights. The assistant captures anonymized interaction data for demand forecasting, assortment optimization and targeted promotions thus enabling smarter merchandising strategies.

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The deployment of AI sommelier followed a structured multi-phase roadmap ensuring technical precision, active user engagement and seamless integration with existing retail operations.
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1. Knowledge Base Creation and Model Adaptation – Building a Realtime Multimodal Conversational AI trained on a domain-specific beverage ontology covering varietals, regions, production techniques and pairing logic. Fine-tuning the LLM with the company's product catalogs, sommelier manuals and brand guidelines to ensure professional brand-consistent communication.
2. Multimodal Intelligence – Integrating a computer vision for product identification and "product placement", adding speech recognition models to maintain real-time human inputs, complex hybrid search models for metadata retrieval and real-time SKU mapping and automated pricing updates.
3. Store Mapping – Developing dynamic in-store navigation tied to digital floor plans and shelf coordinates.
4. Design – Designing kiosk UX with intuitive pathways for browsing, asking questions and locating items.
5. Integration and Testing – Integrating the assistant with POS, CRM and analytics dashboards, conducting in-store pilots, refining interaction tone, product recommendations and navigation accuracy based on feedback.
6. Scaling and Continuous Learning – Rolling out across multiple store formats, continuously enriching the AI’s knowledge with seasonal assortments and customer behavior data.
7. Analytics – Introducing advanced analytics to measure engagement, dwell time and cross-category conversion uplift.

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As a result of implementation, the AI Sommelier redefined the retail experience for customers, blending convenience, education, storytelling and entertainment.

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• The AI assistant delivered sommelier-level guidance instantly and consistently across stores, transforming the browsing process into an experience with product stories and pairing suggestions. The shift to AI-based assistance improved overall service efficiency by 32% and optimized staff allocation during peak hours without increasing headcount.
• Personalized recommendations and data-driven pairing logic boosted conversion rates and expanded the discovery of new products. As a result, the average basket size increased by 16% and cross-category sales (e.g. accessories, snacks and glassware) grew by 11%.
• Consistent expert-level communication across all locations enhanced brand reliability and customer trust reflecting in a 19% rise in satisfaction scores and a measurable improvement in customer return rates.

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Ultimately, the project positioned the retailer as a frontrunner in intelligent experiential retail, merging AI precision with the artistry of wine expertise to drive measurable business growth and lasting customer loyalty.