Catapult Customer Service With Internal AI Chat Systems

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Catapult Customer Service With Internal AI Chat Systems
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Daniel Fallmann is founder and CEO of Mindbreeze, a leader in enterprise search, applied artificial intelligence and knowledge management. Read Daniel Fallmann's full executive profile here.

We all know that customer service is a core space where companies can improve to maintain an edge against their competitors.highlights"51 customer service statistics you need to know." Two of the most interesting statistics shared are that 73% of consumers will switch to a competitor after multiple bad experiences, and companies focusing on CX also increase their revenue by 80%.

Large language models, such as OpenAI's GPT series, have revolutionized the field of natural language processing . By leveraging large language models within internal AI chat systems, companies can tap into their numerous knowledge repositories to provide accurate and relevant information to customers.

In the context of internal AI chat systems, RAG enhances the efficiency of knowledge retrieval by incorporating a retrieval mechanism alongside the generative model. By pre-indexing relevant knowledge sources, such as company databases or even the internet, RAG can quickly retrieve pertinent information in response to user queries. The generative component then synthesizes this retrieved information into coherent and contextually relevant responses, ensuring accuracy and comprehensiveness.1.

By providing accurate and timely responses to customer inquiries, AI chat systems can enhance the overall satisfaction of customers, leading to increased loyalty and retention.

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