The power of RAG AI: Transforming information access and customer experience

Using AI for effective solutions

We view AI as a powerful tool for designing and building solutions for our customers. It can enhance organizational efficiency, make customer experiences more relevant and effective, and serve as an assistant that, when used correctly, drives results. By integrating Retrieval-Augmented Generation (RAG), we can leverage vast amounts of data to provide more accurate and contextually relevant information, further enhancing the capabilities and effectiveness of our AI solutions.

What is RAG AI?

Retrieval-Augmented-Generation is a method for enhancing the output of a large language model (an advanced AI designed to understand and generate human-like text) by using information from a trusted source before creating a response.

Large Language Models (LLMs) are trained on extensive datasets and utilize billions of parameters to perform tasks such as answering questions, translating languages, and completing sentences.

RAG leverages these capabilities by incorporating specific domain knowledge or an organization's internal data without requiring model retraining. This approach is cost-effective and improves the relevance, accuracy, and usefulness of the LLM's output in various applications.

Are you interested in a custom RAG chatbot? Let's make it click!

Whats the difference between RAG AI and ChatGPT?

The main difference between ChatGPT and RAG AI lies in their approach to generating responses. ChatGPT generates responses based solely on the knowledge it was trained on, which is static and has a cut-off date, meaning it does not access external information sources during the response generation process.

In contrast, Retrieval-Augmented Generation (RAG) enhances response generation by retrieving relevant information from external authoritative sources in real-time before generating a response. This allows RAG AI to provide more accurate and relevant answers with up-to-date information.

How can we help your company further with RAG AI?

RAG AI systems, which combine retrieval capabilities with generative AI, offer many benefits to customers and businesses. Firstly, they provide better access to information by gathering data from multiple sources and giving clear, useful answers. This is more helpful than traditional search engines, which just list links to websites. RAG AI systems can also create personalised experiences for customers. They understand the context of questions and provide specific, relevant answers. This means customers get more accurate and tailored information, making their experience more satisfying and engaging.

First, we are going to look at your content. We’re going to put this content into a "brain", that later will become your business expert. The user can use this brain to get some answers. To give you an example: We’ve done a RAG AI setup for a government agency, where customers could ask their specific company-related questions such as: “I would like to go on parental leave, am I entitled to it?” Our RAG AI setup will ask you to give it some more relevant information by for example logging in to your account.

The major advantage here is, that it doesn’t cooperate with ChatGPT. All your (personal) questions stays within the related company by operating with a private mode.

The easiest way to make this visible is to use RAG AI in a chatbot. It’s not a ‘normal’ chatbot that we all know, but with this one you can make real conversations, like a real assistant. But we can also implement it in your search bar. Back to our government agency project, you’ve got a question about parental leave and you start typing in the search bar. Instead of leading you as a user to a specific page, RAG AI will ask you some more related questions to help you more specific.