Generative AI

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How Anomalo solves unstructured data quality issues to deliver trusted assets for AI with AWS

This post is co-written with Vicky Andonova and Jonathan Karon from Anomalo. Generative AI has rapidly evolved from a novelty to a powerful driver of innovation. From summarizing complex legal documents to powering advanced chat-based assistants, AI capabilities are expanding at an increasing pace. While large language models (LLMs) continue to push new boundaries, quality […]

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An innovative financial services leader finds the right AI solution: Robinhood and Amazon Nova

This post is cowritten with Renyu Chen and Dev Tagare from Robinhood. Robinhood has been a pioneer and disruptor in the once staid world of online brokerages. Founded in 2013, the company transformed an industry better known for gatekeeping into an open platform accessible to all. Robinhood pioneered commission-free trading, and harnessed the power of

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Build conversational interfaces for structured data using Amazon Bedrock Knowledge Bases

Organizations manage extensive structured data in databases and data warehouses. Large language models (LLMs) have transformed natural language processing (NLP), yet converting conversational queries into structured data analysis remains complex. Data analysts must translate business questions into SQL queries, creating workflow bottlenecks. Amazon Bedrock Knowledge Bases enables direct natural language interactions with structured data sources.

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How Apollo Tyres is unlocking machine insights using agentic AI-powered Manufacturing Reasoner

This is a joint post co-authored with Harsh Vardhan, Global Head, Digital Innovation Hub, Apollo Tyres Ltd. Apollo Tyres, headquartered in Gurgaon, India, is a prominent international tire manufacturer with production facilities in India and Europe. The company advertises its products under its two global brands: Apollo and Vredestein, and its products are available in

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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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