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Build a generative AI call analyzer front end application

Generative AI and Large Language Models (LLMs) can add conversational style features to your contact center application. This session showcases the step by step guide through a demo on how to build a generative AI call analyzer, a front-end application based on Python Streamlit framework. We walk through how to upload an audio conversation which consist of a contact center recording and then covert audio into transcripts with Amazon Transcribe. We show how to convert text to vector embeddings and use LLMs for creating summarization, sentiment analysis, call analytics, language translation, and Q&A. Walk away with the knowledge you can use to try on a call transcription and analytics use case using LLMs available on Amazon SageMaker JumpStart.
Speaker: Arman Sharma, Senior Solutions Architect, AWS