AI

Build a FinOps agent using Amazon Bedrock with multi-agent capability and Amazon Nova as the foundation model

AI agents are revolutionizing how businesses enhance their operational capabilities and enterprise applications. By enabling natural language interactions, these agents provide customers with a streamlined, personalized experience. Amazon Bedrock Agents uses the capabilities of foundation models (FMs), combining them with APIs and data to process user requests, gather information, and execute specific tasks effectively. The

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Stream ingest data from Kafka to Amazon Bedrock Knowledge Bases using custom connectors

Retrieval Augmented Generation (RAG) enhances AI responses by combining the generative AI model’s capabilities with information from external data sources, rather than relying solely on the model’s built-in knowledge. In this post, we showcase the custom data connector capability in Amazon Bedrock Knowledge Bases that makes it straightforward to build RAG workflows with custom input

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MIT’s McGovern Institute is shaping brain science and improving human lives on a global scale

In 2000, Patrick J. McGovern ’59 and Lore Harp McGovern made an extraordinary gift to establish the McGovern Institute for Brain Research at MIT, driven by their deep curiosity about the human mind and their belief in the power of science to change lives. Their $350 million pledge began with a simple yet audacious vision:

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Add Zoom as a data accessor to your Amazon Q index

For many organizations, vast amounts of enterprise knowledge are scattered across diverse data sources and applications. Organizations across industries seek to use this cross-application enterprise data from within their preferred systems while adhering to their established security and governance standards. This post demonstrates how Zoom users can access their Amazon Q Business enterprise data directly

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The future of quality assurance: Shift-left testing with QyrusAI and Amazon Bedrock

This post is co-written with Ameet Deshpande and Vatsal Saglani from Qyrus. As businesses embrace accelerated development cycles to stay competitive, maintaining rigorous quality standards can pose a significant challenge. Traditional testing methods, which occur late in the development cycle, often result in delays, increased costs, and compromised quality. Shift-left testing, which emphasizes earlier testing

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Automate video insights for contextual advertising using Amazon Bedrock Data Automation

Contextual advertising, a strategy that matches ads with relevant digital content, has transformed digital marketing by delivering personalized experiences to viewers. However, implementing this approach for streaming video-on-demand (VOD) content poses significant challenges, particularly in ad placement and relevance. Traditional methods rely heavily on manual content analysis. For example, a content analyst might spend hours

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