Using transcription confidence scores to improve slot filling in Amazon Lex

When building voice-enabled chatbots with Amazon Lex, one of the biggest challenges is accurately capturing user speech input for slot values. For example, when a user needs to provide their account number or confirmation code, speech recognition accuracy becomes crucial. This is where transcription confidence scores come in to help ensure reliable slot filling. What […]

Improving Retrieval Augmented Generation accuracy with GraphRAG

Customers need better accuracy to take generative AI applications into production. In a world where decisions are increasingly data-driven, the integrity and reliability of information are paramount. To address this, customers often begin by enhancing generative AI accuracy through vector-based retrieval systems and the Retrieval Augmented Generation (RAG) architectural pattern, which integrates dense embeddings to […]