Improving customer service interactions using RAG

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By José Ignacio Orlando

March 13, 2024

Retrieval-Augmented Generation (RAG) is revolutionizing question answering. It goes beyond the limitations of static FAQs by enabling chatbots to interact with users in natural language (any language!), answer questions from diverse data sources, and generate human-like responses instantly. This can create very important advantages for your business, since it’s a 24/7 service that any person can use, with the added benefit of being able to locate and extract information from all types of sources.

In our previous articles we covered the fundamental aspects of this technology, paying particular attention to how they work internally and which type of data sources can be connected with these tools. In upcoming articles, we will illustrate how RAG systems can be leveraged to tackle industry-specific challenges. But today, we’ll explore how RAG-based customer service interactions work and their impact.

For decades now, chatbots have been a mainstay in customer service as they offer a first line of defense for fielding basic inquiries and handling routine requests. However, early versions struggled to grasp the nuances of human language, leading to misinterpretations of user intent and ultimately frustrating customer interactions.

With the emergence of Large Language Models (LLMs), the landscape changed drastically.  The generative capabilities of these algorithms allows them to not only comprehend user queries with remarkable precision but also seamlessly access and process information from vast knowledge bases to answer questions properly. Think of that knowledge base as a digital library specifically curated for the chatbot, containing relevant information about products, services, policies, and more.  This newfound ability empowers chatbots to deliver accurate and comprehensive answers to customer questions in a matter of seconds, mimicking the natural flow of human conversation

The impact on customer service is transformative.  RAG-powered chatbots can efficiently handle a significant volume of customer inquiries, freeing up valuable human resources to focus on more complex issues that require a personal touch. This translates to a significant improvement in both efficiency and user experience. Customers can now expect their questions to be addressed promptly and accurately, leading to a more positive brand perception. Additionally, human agents are empowered to dedicate their time and expertise to resolving intricate customer concerns, fostering stronger customer relationships.  In essence, RAG-powered chatbots act as a bridge between customers and human agents, streamlining the overall customer service experience.

This technology has already shown a transformative impact on this field. According to a Salesforce report, 98% of service professionals using automation report that it saves time, with 50% of them having experienced a major improvement in their workflows. Similarly, a recent paper has shown an increase in the productivity of customer support agents of over 14% thanks to the incorporation of these tools.

Don’t let your competitors steal the lead in customer service satisfaction!  Discover how RAG-powered chatbots can give your business a competitive edge by providing faster, more accurate, and personalized customer interactions.  Contact our AI specialists today at for a free consultation to discuss how Arionkoder can help you build custom chatbots that will delight your customers and empower your human agents.