Amazon Machine Learning

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Building cost-effective RAG applications with Amazon Bedrock Knowledge Bases and Amazon S3 Vectors

Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon Machine Learning, Artificial Intelligence /

Vector embeddings have become essential for modern Retrieval Augmented Generation (RAG) applications, but organizations face significant cost challenges as they scale. As knowledge bases grow and require more granular embeddings, many vector databases that rely on high-performance storage such as SSDs or in-memory solutions become prohibitively expensive. This cost barrier often forces organizations to limit […]

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How PayU built a secure enterprise AI assistant using Amazon Bedrock

AI/ML, Amazon Bedrock, Amazon Bedrock Agents, Amazon Bedrock Guardrails, Amazon Bedrock Knowledge Bases, Amazon Machine Learning, Customer Solutions, Generative AI /

This is a guest post co-written with Rahul Ghosh, Sandeep Kumar Veerlapati, Rahmat Khan, and Mudit Chopra from PayU. PayU offers a full-stack digital financial services system that serves the financial needs of merchants, banks, and consumers through technology. As a Central Bank-regulated financial institution in India, we recently observed a surge in our employees’

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How Rapid7 automates vulnerability risk scores with ML pipelines using Amazon SageMaker AI

Amazon Machine Learning, Amazon SageMaker AI, Customer Solutions, DevOps /

This post is cowritten with Jimmy Cancilla from Rapid7. Organizations are managing increasingly distributed systems, which span on-premises infrastructure, cloud services, and edge devices. As systems become interconnected and exchange data, the potential pathways for exploitation multiply, and vulnerability management becomes critical to managing risk. Vulnerability management (VM) is the process of identifying, classifying, prioritizing,

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Build secure RAG applications with AWS serverless data lakes

Amazon Machine Learning, Amazon SageMaker, Amazon SageMaker Data & AI Governance, Amazon SageMaker Lakehouse, Amazon Simple Storage Service (S3), Best Practices, Customer Solutions, Generative AI, Technical How-to /

Data is your generative AI differentiator, and successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Traditional data architectures often struggle to meet the unique demands of generative such as applications. An effective generative AI data strategy requires several key components like seamless integration of diverse data sources,

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Use K8sGPT and Amazon Bedrock for simplified Kubernetes cluster maintenance

Amazon Bedrock, Amazon Elastic Kubernetes Service, Amazon Machine Learning, Amazon SageMaker, Amazon SageMaker AI, Artificial Intelligence /

As Kubernetes clusters grow in complexity, managing them efficiently becomes increasingly challenging. Troubleshooting modern Kubernetes environments requires deep expertise across multiple domains—networking, storage, security, and the expanding ecosystem of CNCF plugins. With Kubernetes now hosting mission-critical workloads, rapid issue resolution has become paramount to maintaining business continuity. Integrating advanced generative AI tools like K8sGPT and

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Configure fine-grained access to Amazon Bedrock models using Amazon SageMaker Unified Studio

Amazon Bedrock, Amazon Machine Learning, Amazon SageMaker Unified Studio, Artificial Intelligence, AWS Identity and Access Management (IAM), Security, Identity, & Compliance, Technical How-to /

Enterprises adopting advanced AI solutions recognize that robust security and precise access control are essential for protecting valuable data, maintaining compliance, and preserving user trust. As organizations expand AI usage across teams and applications, they require granular permissions to safeguard sensitive information and manage who can access powerful models. Amazon SageMaker Unified Studio addresses these

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Accelerate AI development with Amazon Bedrock API keys

Amazon Bedrock, Amazon Machine Learning, Announcements, Artificial Intelligence, Foundation models /

Today, we’re excited to announce a significant improvement to the developer experience of Amazon Bedrock: API keys. API keys provide quick access to the Amazon Bedrock APIs, streamlining the authentication process so that developers can focus on building rather than configuration. CamelAI is an open-source, modular framework for building intelligent multi-agent systems for data generation,

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Combat financial fraud with GraphRAG on Amazon Bedrock Knowledge Bases

Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon Machine Learning, Amazon Neptune Analytics, Technical How-to /

Financial fraud detection isn’t just important to banks—it’s essential. With global fraud losses surpassing $40 billion annually and sophisticated criminal networks constantly evolving their tactics, financial institutions face an increasingly complex threat landscape. Today’s fraud schemes operate across multiple accounts, institutions, and channels, creating intricate webs designed specifically to evade detection systems. Financial institutions have

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Classify call center conversations with Amazon Bedrock batch inference

Amazon Bedrock, Amazon Machine Learning, Artificial Intelligence, Intermediate (200) /

In this post, we demonstrate how to build an end-to-end solution for text classification using the Amazon Bedrock batch inference capability with the Anthropic’s Claude Haiku model. Amazon Bedrock batch inference offers a 50% discount compared to the on-demand price, which is an important factor when dealing with a large number of requests. We walk

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Transforming network operations with AI: How Swisscom built a network assistant using Amazon Bedrock

Amazon Machine Learning, Artificial Intelligence, Customer Solutions, Generative AI /

In the telecommunications industry, managing complex network infrastructures requires processing vast amounts of data from multiple sources. Network engineers often spend considerable time manually gathering and analyzing this data, taking away valuable hours that could be spent on strategic initiatives. This challenge led Swisscom, Switzerland’s leading telecommunications provider, to explore how AI can transform their

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