Optimization of Language Models: Implementation of Coveo Passage Retrieval on Amazon Bedrock

In an environment where generative AI is transforming business operations, a crucial challenge arises: ensuring that large language models provide accurate and reliable responses. The lack of precision in the data that feed these models can generate ambiguous responses, affecting users' trust and the credibility of organizations.

To face this challenge, Coveo, in collaboration with Amazon Web Services, has developed the Ticket Recovery API. This solution aims to strengthen the reliability of applications based on large language models by providing relevant and contextual business knowledge that enriches the generated responses. In Retrieval-Augmented Generation systems, data retrieval is a complex component, focused on extracting the most precise information from the available sources.

Coveo's AI-Relevance Platform, together with Amazon Bedrock Agents, offers an advanced enterprise search service that respects corporate permission models, ensuring robust connectivity. Coveo's machine learning algorithms optimize the relevance of content, enabling Amazon Bedrock Agents to provide answers grounded in complex business data.

The Passages Retrieval API, based on a unified hybrid index, identifies relevant documents and extracts key information with metadata, such as URLs for citations. This process guarantees the security and relevance of real-time responses.

Thanks to this solution, it is possible to develop powerful assistants powered by large language models that can access sensitive business knowledge to respond to queries from customers, employees, or sales teams. By integrating the API with the Amazon Bedrock Agents, organizations ensure that the responses generated by artificial intelligence are based on accurate and reliable information.

Coveo also guarantees data protection through a native permissions model, preventing leaks of sensitive information and improving search performance. A deep analysis of content usage allows organizations to optimize the quality of the generated responses, positively impacting their business.

This innovative approach redefines Retrieval-Augmented Generation systems by going beyond conventional vector search, offering a dynamic and intelligent retrieval process that meets business needs, reinforcing Coveo's commitment to reliable and secure generative AI experiences.

Mariana G.
Mariana G.
Mariana G. is a European journalist and editor of current news in Madrid, Spain, and around the world. With more than 15 years of experience in the field, they specialize in covering events of local and international relevance, offering in-depth analyses and detailed reports. Your daily work includes supervising the drafting, selecting topics of interest, and editing articles to ensure the highest quality of information. Mariana is known for her rigorous approach and her ability to communicate complex news in a clear and accessible way to a diverse audience.

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