What kind of AI Chatbot do you need? | SoftwareMill

"An AI Chatbot is an instruction-tuned Large Language Model (LLM). Such a chatbot can provide fast, accurate, and relevant answers to questions it is faced with. However, it is limited to the information, text tone, format, and style it was trained on. The Retrieval Augmented Generation (RAG-Chatbot) technique enables connecting the AI Chatbot with your internal, private organization's documentation. It is capable of answering questions based on the provided knowledge base."

"Users can ask questions and get answers based on the documentation, even though the model has never seen it during the training process (your internal documentation stays private and safe!). Correct documents are retrieved by the AI, based on the user query, and appended to the query as a context before feeding to the AI Chatbot. Building the RAG-Chatbot requires parsing all the organization's documentation to the correct format and making a few design choices."

"Cloud API-based solutions are great in terms of development speed, Proof-of-Concept validation, and small usage traffic. They also offer regular model updates free of charge. However, they come with many limitations: Limited customization. Not price-efficient for very large traffic. It might not be safe enough for highly confidential data. Foundation model It is the best approach in most cases. It is quick to implement and works reasonably well."

An instruction-tuned LLM chatbot provides fast, accurate, and relevant answers but is limited to its training data, tone, format, and style. Retrieval Augmented Generation (RAG) connects the chatbot to private organizational documentation so the chatbot can answer from the provided knowledge base while keeping internal documents private. RAG retrieves relevant documents based on user queries and appends them as context before querying the model. Building a RAG-Chatbot requires parsing documentation into the correct formats and making deployment design choices. Cloud API-based hosting offers quick development and automatic updates but limits customization, costs scale with heavy traffic, and may risk confidentiality.

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