Artificial Intelligence
Author: Suren Gunturu
Suren Gunturu is a Data Scientist working in the Generative AI Innovation Center, where he works with various AWS customers to solve high-value business problems. He specializes in building ML pipelines using Large Language Models, primarily through Amazon Bedrock and other AWS Cloud services.
Asure’s approach to enhancing their call center experience using generative AI and Amazon Q in QuickSight
In this post, we explore why Asure used the Amazon Web Services (AWS) post-call analytics (PCA) pipeline that generated insights across call centers at scale with the advanced capabilities of generative AI-powered services such as Amazon Bedrock and Amazon Q in QuickSight. Asure chose this approach because it provided in-depth consumer analytics, categorized call transcripts around common themes, and empowered contact center leaders to use natural language to answer queries. This ultimately allowed Asure to provide its customers with improvements in product and customer experiences.
How Tealium built a chatbot evaluation platform with Ragas and Auto-Instruct using AWS generative AI services
In this post, we illustrate the importance of generative AI in the collaboration between Tealium and the AWS Generative AI Innovation Center (GenAIIC) team by automating the following: 1/ Evaluating the retriever and the generated answer of a RAG system based on the Ragas Repository powered by Amazon Bedrock, 2/ Generating improved instructions for each question-and-answer pair using an automatic prompt engineering technique based on the Auto-Instruct Repository. An instruction refers to a general direction or command given to the model to guide generation of a response. These instructions were generated using Anthropic’s Claude on Amazon Bedrock, and 4/ Providing a UI for a human-based feedback mechanism that complements an evaluation system powered by Amazon Bedrock.