Building a Custom Robust Retrieval Augmented Generation Chatbot

In today’s emerging AI market landscape, chatbots are a much desired additional value for many businesses and sectors. Driven by tremendous funding and highly active open-source innovation and research, the bet on generative AI, chatbots particularly, is growing heavier as the technology becomes more powerful and reliable by the minute. Assuming reliability, there are still two immediate concerns for businesses willing to integrate AI chatbots into their workflow, products, and services: full customizability, and data privacy. While the stakes for data privacy are fairly known, full customizability is an integral, yet often undervalued, property of robust chatbot systems. Even within a single business, the needs can be very diverse and certainly evolve with time. Therefore, a robust chatbot system should be fully customizable in that it can be tailored to today’s needs without being too rigid in anticipation of future requirements and data. At Astrafy SA, I built a robust Retrieval Augmented Generation (RAG) chatbot named Astrabot, designed to fulfill any role that requires information retrieval and for any use case. Just feed the system your text documents in “plug-and-play”-style, and it will become an expert at answering any question about these documents in seconds and in the most human-like fashion, while still being able to carry out normal conversations that do not require information retrieval. <a href="https://medium.astrafy.io/building-a-custom-robust-retrieval-augmented-generation-chatbot-8ab73a371eb8">Visit Now</a>