Multi-tenant RAG implementation with Amazon Bedrock and Amazon OpenSearch Service for SaaS using JWT

Favorite In recent years, the emergence of large language models (LLMs) has accelerated AI adoption across various industries. However, to further augment LLMs’ capabilities and effectively use up-to-date information and domain-specific knowledge, integration with external data sources is essential. Retrieval Augmented Generation (RAG) has gained attention as an effective approach

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Shared by AWS Machine Learning July 23, 2025

Beyond accelerators: Lessons from building foundation models on AWS with Japan’s GENIAC program

Favorite In 2024, the Ministry of Economy, Trade and Industry (METI) launched the Generative AI Accelerator Challenge (GENIAC)—a Japanese national program to boost generative AI by providing companies with funding, mentorship, and massive compute resources for foundation model (FM) development. AWS was selected as the cloud provider for GENIAC’s second

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Shared by AWS Machine Learning July 22, 2025

Use generative AI in Amazon Bedrock for enhanced recommendation generation in equipment maintenance

Favorite In the manufacturing world, valuable insights from service reports often remain underutilized in document storage systems. This post explores how Amazon Web Services (AWS) customers can build a solution that automates the digitisation and extraction of crucial information from many reports using generative AI. The solution uses Amazon Nova

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Shared by AWS Machine Learning July 21, 2025

Kyruus builds a generative AI provider matching solution on AWS

Favorite This post was written with Zach Heath of Kyruus Health. When health plan members need care, they shouldn’t need a dictionary. Yet millions face this exact challenge—describing symptoms in everyday language while healthcare references clinical terminology and complex specialty classifications. This disconnect forces members to become amateur medical translators,

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Shared by AWS Machine Learning July 21, 2025

Build an AI-powered automated summarization system with Amazon Bedrock and Amazon Transcribe using Terraform

Favorite Extracting meaningful insights from unstructured data presents significant challenges for many organizations. Meeting recordings, customer interactions, and interviews contain invaluable business intelligence that remains largely inaccessible due to the prohibitive time and resource costs of manual review. Organizations frequently struggle to efficiently capture and use key information from these

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Shared by AWS Machine Learning July 21, 2025