QnABot on AWS (an AWS Solution) now provides access to Amazon Bedrock foundational models (FMs) and Knowledge Bases for Amazon Bedrock, a fully managed end-to-end Retrieval Augmented Generation (RAG) workflow. You can now provide contextual information from your private data sources that can be used to create rich, contextual, conversationalContinue Reading
As conversational artificial intelligence (AI) agents gain traction across industries, providing reliability and consistency is crucial for delivering seamless and trustworthy user experiences. However, the dynamic and conversational nature of these interactions makes traditional testing and evaluation methods challenging. Conversational AI agents also encompass multiple layers, from Retrieval Augmented GenerationContinue Reading
Traditionally, finding relevant information from documents has been a time-consuming and often frustrating process. Manually sifting through pages upon pages of text, searching for specific details, and synthesizing the information into coherent summaries can be a daunting task. This inefficiency not only hinders productivity but also increases the risk ofContinue Reading
With the advent of generative artificial intelligence (AI), foundation models (FMs) can generate content such as answering questions, summarizing text, and providing highlights from the sourced document. However, for model selection, there is a wide choice from model providers, like Amazon, Anthropic, AI21 Labs, Cohere, and Meta, coupled with discreteContinue Reading
