In the ever-evolving landscape of Artificial Intelligence (AI), where we see new breakthroughs and innovations almost daily, the acceleration of AI application alongside technologies such as ChatGPT has become nothing short of phenomenal. However, amid this rapid development, it is crucial to recognize that as a business, we need to strategically focus on specific technologies that can truly drive and shape the adoption of AI.
In this dynamic area, two technologies are emerging as promising beacons for Retail: Retrieval Augmented Generation (RAG) and Reasoning and Acting (ReAct). It’s not just about riding the AI wave, it’s about leveraging specific tools that will drive companies to adopt AI and lead to predictive insights, personalized interactions and ultimately success in the market. Let’s drive into the transformative power of RAG and ReAct and how they can redefine the way retailers engage, innovate, and thrive in the AI-driven age.
Get ready for an insightful exploration of the areas of AI in retail as we present a three-part blog series. In part one, we dive into the transformative power of RAG and unravel how it predicts, personalizes and drives prosperity in retail strategies.
The exploration continues in part two, where we explore ReAct and its dynamic approach to problem solving, showing you how it adds an extra layer of intelligence in retail strategies.
Finally, the third and concluding part, we take a deep dive into the capabilities of the SAP Business Technology Platform (BTP). Discover how the BTP, with its SAP HANA Vector Engine (available Q1/2024) and the robust SAP AI Foundation, becomes the backbone and enables the seamless integration of RAG and ReAct into the customer landscape to ensure a future-proof and AI-powered retail ecosystem.
Retrieval Augmented Generation (RAG)
Retrieval Augmented Generation is emerging as a leading application of Large Language Models (LLMs), demonstrating its capabilities in seamlessly integrating them with an organization's own data.
Illustration of RAG pipeline
How RAG works:
- Ingestion:
Documents and information are broken down into smaller segments, creating Embeddings (external link) that are stored in a vector storage, such as the SAP HANA Vector Engine (available Q1/2024) announced at this years SAP TechEd in Bangalore.
- Retrieval:
When a user makes a request, the system initiates a retrieval process where the vector store is queried to extract the most relevant context for each specific request. The context relevance evaluation metrics are critical at this stage as they ensure that the retrieved context seamlessly matches the user's query.
Evaluation of context-related metrics:
- Context relevance: Is the context extracted from the vector store relevant to the user's query? This metric ensures that the information retrieved is contextually consistent with the user's intent.
- Groundedness: Is the answer supported by the context? This metric evaluates the strength of the connection between the retrieved context and the subsequent response and ensures that the generated output is firmly anchored in the context provided.
- Answer relevance: Is the response relevant to the user's request? This metric evaluates the overall relevance of the synthesized response and ensures that it directly addresses the user's request.
- Synthesis:
RAG combines the retrieved context with the power of the LLM to produce a comprehensive response that incorporates both the contextual information and the capabilities of the language model. This synthesis ensures a nuanced and informed output tailored to the user’s needs.
Potential Use Cases:
- Personalized Buying Advice for Customers:
Imagine a scenario where a customer wants personalized buying advice at a retail store. RAG can transform this interaction by seamlessly integrating LLM with proprietary data. When a customer initiates a request for product recommendations or seeks personalized advice, the RAG system can capture the customer's preferences and previous interactions, retrieve relevant information from the vector store and create a tailored response. This ensures that customers receive individualized buying advice, enhancing their overall shopping experience and promoting a sense of personalization.
- Comprehensive KPI Analysis for Store Managers:
For store managers who want to make data-driven decisions, RAG is a valuable tool. When a store manager requests information on Key Performance Indicators (KPIs) for a specific store on a particular day, the RAG system can process this request efficiently. Through the pipeline of ingestion, retrieval, and synthesis, RAG extracts relevant data from the vector storage, combines it with the latest KPI metrics, and presents a comprehensive overview of the store's performance on the specified day. This enables store managers to make informed decisions, identify trends and optimize operations based on real-time data.
These use cases demonstrate how RAG can be used to provide dynamic and tailored solutions in retail scenarios that improve both customer interactions and managerial decision-making processes. This opens up a range of possibilites for personalized and data-driven retail experiences, based on LLMs and enterprise data.
Conclusion:
Prediction, personalization and prosperity - these are not just wishes, but the promises that Retrieval Augmented Generation delivers in retail. As AI continues its rapid rise, RAG is at the forefront, providing retailers with a transformative tool to not only keep pace with change, but to lead the way to a smarter and more prosperous future.
If you would like to learn more about RAG's technical architecture on the SAP Business Technology Platform, we invite you to explore our comprehensive reference architecture here, based on the use case of leveraging customer support with RAG. Also, stay tuned for the third part of our series, where we'll look at the capabilities of the SAP HANA Vector Engine and its central role in boosting the performance and efficiency of RAG in your retail ecosystem. The future of retail is not only AI-driven, but also strategically designed for success. Join us on this transformative journey!
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