Amazon Bedrock Guardrails

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Detect Amazon Bedrock misconfigurations with Datadog Cloud Security

AI/ML, Amazon Bedrock, Amazon Bedrock Agents, Amazon Bedrock Guardrails, Generative AI, Monitoring and observability, Partner solutions, Security /

This post was co-written with Nick Frichette and Vijay George from Datadog.  As organizations increasingly adopt Amazon Bedrock for generative AI applications, protecting against misconfigurations that could lead to data leaks or unauthorized model access becomes critical. The AWS Generative AI Adoption Index, which surveyed 3,739 senior IT decision-makers across nine countries, revealed that 45% […]

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Empowering students with disabilities: University Startups’ generative AI solution for personalized student pathways

Amazon Bedrock, Amazon Bedrock Agents, Amazon Bedrock Guardrails, Amazon Bedrock Knowledge Bases, Customer Solutions /

This post was co-authored with Laura Lee Williams and John Jabara from University Startups. University Startups, headquartered in Bethesda, MD, was founded in 2020 to empower high school students to expand their education beyond a traditional curriculum. University Startups is focused on special education and related services in school districts throughout the US. After students

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How Nippon India Mutual Fund improved the accuracy of AI assistant responses using advanced RAG methods on Amazon Bedrock

Amazon Bedrock, Amazon Bedrock Guardrails, Amazon Bedrock Knowledge Bases, Amazon Machine Learning, Artificial Intelligence, Customer Solutions /

This post is co-written with Abhinav Pandey from Nippon Life India Asset Management Ltd. Accurate information retrieval through generative AI-powered assistants is a popular use case for enterprises. To reduce hallucination and improve overall accuracy, Retrieval Augmented Generation (RAG) remains the most commonly used method to retrieve reliable and accurate responses that use enterprise data

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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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Tailor responsible AI with new safeguard tiers in Amazon Bedrock Guardrails

Amazon Bedrock, Amazon Bedrock Guardrails, Artificial Intelligence, Best Practices, Generative AI, Responsible AI, Technical How-to, Thought Leadership /

Amazon Bedrock Guardrails provides configurable safeguards to help build trusted generative AI applications at scale. It provides organizations with integrated safety and privacy safeguards that work across multiple foundation models (FMs), including models available in Amazon Bedrock, as well as models hosted outside Amazon Bedrock from other model providers and cloud providers. With the standalone

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Automate customer support with Amazon Bedrock, LangGraph, and Mistral models

Amazon Bedrock, Amazon Bedrock Guardrails, Generative AI, Intermediate (200), Technical How-to /

AI agents are transforming the landscape of customer support by bridging the gap between large language models (LLMs) and real-world applications. These intelligent, autonomous systems are poised to revolutionize customer service across industries, ushering in a new era of human-AI collaboration and problem-solving. By harnessing the power of LLMs and integrating them with specialized tools

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Build responsible AI applications with Amazon Bedrock Guardrails

Amazon Bedrock, Amazon Bedrock Guardrails, Generative AI, Intermediate (200), Technical How-to /

As organizations embrace generative AI, they face critical challenges in making sure their applications align with their designed safeguards. Although foundation models (FMs) offer powerful capabilities, they can also introduce unique risks, such as generating harmful content, exposing sensitive information, being vulnerable to prompt injection attacks, and returning model hallucinations. Amazon Bedrock Guardrails has helped

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Build a serverless audio summarization solution with Amazon Bedrock and Whisper

Amazon API Gateway, Amazon Bedrock, Amazon Bedrock Guardrails, Amazon EventBridge, Application Integration, Architecture, AWS Step Functions, Best Practices, Generative AI, Technical How-to /

Recordings of business meetings, interviews, and customer interactions have become essential for preserving important information. However, transcribing and summarizing these recordings manually is often time-consuming and labor-intensive. With the progress in generative AI and automatic speech recognition (ASR), automated solutions have emerged to make this process faster and more efficient. Protecting personally identifiable information (PII)

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HERE Technologies boosts developer productivity with new generative AI-powered coding assistant

Amazon Bedrock, Amazon Bedrock Guardrails, Amazon Bedrock Knowledge Bases, Customer Solutions, Generative AI /

This blog post is co-written with Jonas Neuman from HERE Technologies.  HERE Technologies, a 40-year pioneer in mapping and location technology, collaborated with the AWS Generative AI Innovation Center (GenAIIC) to enhance developer productivity with a generative AI-powered coding assistant. This innovative tool is designed to enhance the onboarding experience for HERE’s self-service Maps API

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Detect hallucinations for RAG-based systems

Amazon Bedrock, Amazon Bedrock Guardrails, Best Practices, Generative AI /

With the rise of generative AI and knowledge extraction in AI systems, Retrieval Augmented Generation (RAG) has become a prominent tool for enhancing the accuracy and reliability of AI-generated responses. RAG is as a way to incorporate additional data that the large language model (LLM) was not trained on. This can also help reduce generation

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