Generative AI

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Extend your Amazon Q Business with PagerDuty Advance data accessor

This blog post is co-written with Jacky Leybman from PagerDuty. As organizations scale their digital operations, they face unprecedented challenges in managing and extracting value from their vast data ecosystems, particularly when it comes to data accessibility and quality. The complexity of modern IT operations demands solutions that can efficiently integrate, process, and deliver actionable […]

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Deploy Qwen models with Amazon Bedrock Custom Model Import

We’re excited to announce that Amazon Bedrock Custom Model Import now supports Qwen models. You can now import custom weights for Qwen2, Qwen2_VL, and Qwen2_5_VL architectures, including models like Qwen 2, 2.5 Coder, Qwen 2.5 VL, and QwQ 32B. You can bring your own customized Qwen models into Amazon Bedrock and deploy them in a fully managed, serverless environment—without having to

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Build generative AI solutions with Amazon Bedrock

Generative AI is revolutionizing how businesses operate, interact with customers, and innovate. If you’re embarking on the journey to build a generative AI-powered solution, you might wonder how to navigate the complexities involved from selecting the right models to managing prompts and enforcing data privacy. In this post, we show you how to build generative

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How Netsertive built a scalable AI assistant to extract meaningful insights from real-time data using Amazon Bedrock and Amazon Nova

This post was co-written with Herb Brittner from Netsertive. Netsertive is a leading digital marketing solutions provider for multi-location brands and franchises, helping businesses maximize local advertising, improve engagement, and gain deep customer insights. With a growing demand in providing more actionable insights from their customer call tracking data, Netsertive needed a solution that could

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Accelerating Articul8’s domain-specific model development with Amazon SageMaker HyperPod

This post was co-written with Renato Nascimento, Felipe Viana, Andre Von Zuben from Articul8. Generative AI is reshaping industries, offering new efficiencies, automation, and innovation. However, generative AI requires powerful, scalable, and resilient infrastructures that optimize large-scale model training, providing rapid iteration and efficient compute utilization with purpose-built infrastructure and automated cluster management. In this

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How VideoAmp uses Amazon Bedrock to power their media analytics interface

This post was co-written with Suzanne Willard and Makoto Uchida from VideoAmp. In this post, we illustrate how VideoAmp, a media measurement company, worked with the AWS Generative AI Innovation Center (GenAIIC) team to develop a prototype of the VideoAmp Natural Language (NL) Analytics Chatbot to uncover meaningful insights at scale within media analytics data

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Adobe enhances developer productivity using Amazon Bedrock Knowledge Bases

Adobe Inc. excels in providing a comprehensive suite of creative tools that empower artists, designers, and developers across various digital disciplines. Their product landscape is the backbone of countless creative projects worldwide, ranging from web design and photo editing to vector graphics and video production. Adobe’s internal developers use a vast array of wiki pages,

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Amazon Nova Lite enables Bito to offer a free tier option for its AI-powered code reviews

This post is co-written by Amar Goel, co-founder and CEO of Bito. Meticulous code review is a critical step in the software development process, one that helps delivery high-quality code that’s ready for enterprise use. However, it can be a time-consuming process at scale, when experts must review thousands of lines of code, looking for

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

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

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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