RAGbot is a central repository of knowledge that rests within an organisation, packaged into a simple conversational interface capable of “chatting” with employees easily. It is based on Retrieval-Augmented Generation (from which the acronym “RAG” is derived), a method used in AI and machine learning to enhance the accuracy and relevance of generated text. Think ChatGPT, but with intimate knowledge of your specific organisational context.

The barrier to entry is low – anyone can interact with a RAGbot a conversational way – and the information is accurate. It transforms how a company approaches presentations, financial forecasts, customer engagements and employee relations.

In addition to accessibility, RAGbot provides companies with:

• The opportunity to automate knowledge sharing, translating into an optimised operating environment and measurable time savings.

• Immediate access to critical information across costs, services and customer profiles, significantly improving customer service and engagement.

The technology powering RAGbot is also built on trusted and incredibly capable foundations. Auxo Digital uses Amazon Bedrock to create the foundational RAG model and then enhances it with an S3 bucket in Amazon for file storage. This is then used to create the knowledge base with OpenSearch to vectorise the database from within Amazon Bedrock. This is deployed on Claude by Anthropic, one of the best models available on the market today. This is then automated or turned into an application using APIs – integration dependent on what the business needs – and workflows are created using a lambda function within Amazon.