jtel RAG Bot

Rag Bot Features

Perfect customer service with jtel’s Rag Bot

A RAG bot is a chat bot or voice bot that uses the RAG (Retrieval-Augmented Generation) framework. This type of bot combines traditional information retrieval techniques with generative language modelling to provide more accurate, relevant and contextual answers.

RAG (Retrieval-Augmented Generation) is an AI approach that combines traditional information retrieval (such as searches and databases) with generative large language models (LLMs). This combination improves the accuracy and relevance of the generated content by integrating your data and general knowledge with the language skills of LLMs.

RAG works in several steps:

Pre-processing:

Advanced search algorithms are used to collect information from external sources (websites, databases, etc.) and prepare this data by cleansing and organising it.

Generation:

The cleansed information is then fed into the LLM, enriching its context and allowing it to generate more accurate and engaging responses.

Overall, RAG improves generative AI results by providing more relevant and up-to-date information.

jtel Multichannel Contact Center Software

Advantages of jtel RAG Bot

• RAG Bots can access a variety of data sources (such as databases, websites, or specialised documents) and search them efficiently to retrieve relevant information.
• Structured indexing helps to optimise the retrieval process.
• Relief for your hotlines. This means that the RAG Bot can access a much larger knowledge base than just the knowledge embedded in its model.

• Retrieving current and relevant data increases the likelihood that the bot will provide more precise and contextually appropriate answers.
• This is particularly advantageous for questions that require specific expertise or up-to-date information.

• A RAG Bot can retrieve information that is regularly updated.
• This means that the bot is always up to date and does not provide outdated data, which can be a problem with traditional models without this retrieval capacity.

• Generative models can sometimes provide false or non-existent information, known as ‘hallucinations’.
• By accessing external sources, the bot can back up its answers with more reliable data, reducing such errors.

• The bot can be configured to retrieve information from different areas or sources, giving it a high degree of flexibility to answer different types of queries.

• RAG bots can also access and efficiently search large amounts of data, making them particularly useful for applications that require large amounts of information

• As the bot is not only reliant on general training data, but is able to access relevant information directly, it can provide answers that are more customised to the user’s individual needs and context.

jtel Multichannel Contact Center Software

RAG Bot features

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