Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

This post is co-authored with Sundeep Sardana, Malolan Raman, Joseph Lam, Maitri Shah and Vaibhav Singh from Verisk. Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry, empowering clients to strengthen operating efficiency, improve underwriting and claims outcomes, combat fraud, and make informed decisions about global risks. … Read more

Announcing general availability of Amazon Bedrock Knowledge Bases GraphRAG with Amazon Neptune Analytics

Today, Amazon Web Services (AWS) announced the general availability of Amazon Bedrock Knowledge Bases GraphRAG (GraphRAG), a capability in Amazon Bedrock Knowledge Bases that enhances Retrieval-Augmented Generation (RAG) with graph data in Amazon Neptune Analytics. This capability enhances responses from generative AI applications by automatically creating embeddings for semantic search and generating a graph of … Read more

Build a Multi-Agent System with LangGraph and Mistral on AWS

Agents are revolutionizing the landscape of generative AI, serving as the bridge between large language models (LLMs) and real-world applications. These intelligent, autonomous systems are poised to become the cornerstone of AI adoption across industries, heralding a new era of human-AI collaboration and problem-solving. By using the power of LLMs and combining them with specialized … Read more

Evaluate RAG responses with Amazon Bedrock, LlamaIndex and RAGAS

In the rapidly evolving landscape of artificial intelligence, Retrieval Augmented Generation (RAG) has emerged as a game-changer, revolutionizing how Foundation Models (FMs) interact with organization-specific data. As businesses increasingly rely on AI-powered solutions, the need for accurate, context-aware, and tailored responses has never been more critical. Enter the powerful trio of Amazon Bedrock, LlamaIndex, and … Read more

Innovating at speed: BMW’s generative AI solution for cloud incident analysis

This post was co-authored with Johann Wildgruber, Dr. Jens Kohl, Thilo Bindel, and Luisa-Sophie Gloger from BMW Group. The BMW Group—headquartered in Munich, Germany—is a vehicle manufacturer with more than 154,000 employees, and 30 production and assembly facilities worldwide as well as research and development locations across 17 countries. Today, the BMW Group (BMW) is the … Read more

Time series forecasting with LLM-based foundation models and scalable AIOps on AWS

Time series forecasting is critical for decision-making across industries. From predicting traffic flow to sales forecasting, accurate predictions enable organizations to make informed decisions, mitigate risks, and allocate resources efficiently. However, traditional machine learning approaches often require extensive data-specific tuning and model customization, resulting in lengthy and resource-heavy development. Enter Chronos, a cutting-edge family of … Read more

Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

Generative AI question-answering applications are pushing the boundaries of enterprise productivity. These assistants can be powered by various backend architectures including Retrieval Augmented Generation (RAG), agentic workflows, fine-tuned large language models (LLMs), or a combination of these techniques. However, building and deploying trustworthy AI assistants requires a robust ground truth and evaluation framework. Ground truth … Read more

Accelerate AWS Well-Architected reviews with Generative AI

Building cloud infrastructure based on proven best practices promotes security, reliability and cost efficiency. To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize … Read more

Dynamic metadata filtering for Amazon Bedrock Knowledge Bases with LangChain

Amazon Bedrock Knowledge Bases offers a fully managed Retrieval Augmented Generation (RAG) feature that connects large language models (LLMs) to internal data sources. It’s a cost-effective approach to improving LLM output so it remains relevant, accurate, and useful in various contexts. It also provides developers with greater control over the LLM’s outputs, including the ability … Read more

Customize DeepSeek-R1 distilled models using Amazon SageMaker HyperPod recipes – Part 1

Increasingly, organizations across industries are turning to generative AI foundation models (FMs) to enhance their applications. To achieve optimal performance for specific use cases, customers are adopting and adapting these FMs to their unique domain requirements. This need for customization has become even more pronounced with the emergence of new models, such as those released … Read more

Reduce conversational AI response time through inference at the edge with AWS Local Zones

Recent advances in generative AI have led to the proliferation of new generation of conversational AI assistants powered by foundation models (FMs). These latency-sensitive applications enable real-time text and voice interactions, responding naturally to human conversations. Their applications span a variety of sectors, including customer service, healthcare, education, personal and business productivity, and many others. … Read more

Pixtral-12B-2409 is now available on Amazon Bedrock Marketplace

Today, we are excited to announce that Pixtral 12B (pixtral-12b-2409), a state-of-the-art 12 billion parameter vision language model (VLM) from Mistral AI that excels in both text-only and multimodal tasks, is available for customers through Amazon Bedrock Marketplace. Amazon Bedrock Marketplace is a new capability in Amazon Bedrock that enables developers to discover, test, and … Read more

Streamline work insights with the Amazon Q Business connector for Smartsheet

Amazon Q Business is a fully managed, generative AI–powered assistant that empowers enterprises to unlock the full potential of their data and organizational knowledge. With Amazon Q Business, you can quickly access answers to questions, generate summaries and content, and complete tasks by using the expertise and information stored across various data sources and enterprise … Read more

Level up your problem-solving and strategic thinking skills with Amazon Bedrock

Organizations across many industries are harnessing the power of foundation models (FMs) and large language models (LLMs) to build generative AI applications to deliver new customer experiences, boost employee productivity, and drive innovation. Amazon Bedrock, a fully managed service that offers a choice of high-performing FMs from leading AI companies, provides the easiest way to … Read more

Optimizing AI implementation costs with Automat-it

This post was written by Claudiu Bota, Oleg Yurchenko, and Vladyslav Melnyk of AWS Partner Automat-it. As organizations adopt AI and machine learning (ML), they’re using these technologies to improve processes and enhance products. AI use cases include video analytics, market predictions, fraud detection, and natural language processing, all relying on models that analyze data … Read more

The end of an era: the final AWS DeepRacer League Championship at re:Invent 2024

AWS DeepRacer League 2024 Championship finalists at re:Invent 2024 The AWS DeepRacer League is the world’s first global autonomous racing league powered by machine learning (ML). Over the past 6 years, a diverse community of over 560,000 builders from more than 150 countries worldwide have participated in the League to learn ML fundamentals hands-on through … Read more

Evaluate healthcare generative AI applications using LLM-as-a-judge on AWS

In our previous blog posts, we explored various techniques such as fine-tuning large language models (LLMs), prompt engineering, and Retrieval Augmented Generation (RAG) using Amazon Bedrock to generate impressions from the findings section in radiology reports using generative AI. Part 1 focused on model fine-tuning. Part 2 introduced RAG, which combines LLMs with external knowledge … Read more

How Pattern PXM’s Content Brief is driving conversion on ecommerce marketplaces using AI

Brands today are juggling a million things, and keeping product content up-to-date is at the top of the list. Between decoding the endless requirements of different marketplaces, wrangling inventory across channels, adjusting product listings to catch a customer’s eye, and trying to outpace shifting trends and fierce competition, it’s a lot. And let’s face it—staying … Read more

How to configure cross-account model deployment using Amazon Bedrock Custom Model Import

In enterprise environments, organizations often divide their AI operations into two specialized teams: an AI research team and a model hosting team. The research team is dedicated to developing and enhancing AI models using model training and fine-tuning techniques. Meanwhile, a separate hosting team is responsible for deploying these models across their own development, staging, … Read more

ByteDance processes billions of daily videos using their multimodal video understanding models on AWS Inferentia2

This is a guest post authored by the team at ByteDance. ByteDance is a technology company that operates a range of content platforms to inform, educate, entertain, and inspire people across languages, cultures, and geographies. Users trust and enjoy our content platforms because of the rich, intuitive, and safe experiences they provide. These experiences are … Read more

How IDIADA optimized its intelligent chatbot with Amazon Bedrock

This post is co-written with Xavier Vizcaino, Diego Martín Montoro, and Jordi Sánchez Ferrer from Applus+ Idiada. In 2021, Applus+ IDIADA, a global partner to the automotive industry with over 30 years of experience supporting customers in product development activities through design, engineering, testing, and homologation services, established the Digital Solutions department. This strategic move … Read more

Accelerate IaC troubleshooting with Amazon Bedrock Agents

Troubleshooting infrastructure as code (IaC) errors often consumes valuable time and resources. Developers can spend multiple cycles searching for solutions across forums, troubleshooting repetitive issues, or trying to identify the root cause. These delays can lead to missed security errors or compliance violations, especially in complex, multi-account environments. This post demonstrates how you can use … Read more

Derive generative AI powered insights from Alation Cloud Services using Amazon Q Business Custom Connector

This blog post is co-written with Gene Arnold from Alation. To build a generative AI-based conversational application integrated with relevant data sources, an enterprise needs to invest time, money, and people. First, you would need build connectors to the data sources. Next you need to index this data to make it available for a Retrieval … Read more

Mistral-Small-24B-Instruct-2501 is now available on SageMaker Jumpstart and Amazon Bedrock Marketplace

Today, we’re excited to announce that Mistral-Small-24B-Instruct-2501—a twenty-four billion parameter large language model (LLM) from Mistral AI that’s optimized for low latency text generation tasks—is available for customers through Amazon SageMaker JumpStart and Amazon Bedrock Marketplace. Amazon Bedrock Marketplace is a new capability in Amazon Bedrock that developers can use to discover, test, and use over 100 … Read more

How Rocket Companies modernized their data science solution on AWS

This post was written with Dian Xu and Joel Hawkins of Rocket Companies. Rocket Companies is a Detroit-based FinTech company with a mission to “Help Everyone Home”. With the current housing shortage and affordability concerns, Rocket simplifies the homeownership process through an intuitive and AI-driven experience. This comprehensive framework streamlines every step of the homeownership … Read more

AWS and DXC collaborate to deliver customizable, near real-time voice-to-voice translation capabilities for Amazon Connect

Providing effective multilingual customer support in global businesses presents significant operational challenges. Through collaboration between AWS and DXC Technology, we’ve developed a scalable voice-to-voice (V2V) translation prototype that transforms how contact centers handle multi-lingual customer interactions. In this post, we discuss how AWS and DXC used Amazon Connect and other AWS AI services to deliver … Read more

Orchestrate an intelligent document processing workflow using tools in Amazon Bedrock

Generative AI is revolutionizing enterprise automation, enabling AI systems to understand context, make decisions, and act independently. Generative AI foundation models (FMs), with their ability to understand context and make decisions, are becoming powerful partners in solving sophisticated business problems. At AWS, we’re using the power of models in Amazon Bedrock to drive automation of … Read more

Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

Large language models (LLMs) excel at generating human-like text but face a critical challenge: hallucination—producing responses that sound convincing but are factually incorrect. While these models are trained on vast amounts of generic data, they often lack the organization-specific context and up-to-date information needed for accurate responses in business settings. Retrieval Augmented Generation (RAG) techniques … Read more

LLM continuous self-instruct fine-tuning framework powered by a compound AI system on Amazon SageMaker

Fine-tuning a pre-trained large language model (LLM) allows users to customize the model to perform better on domain-specific tasks or align more closely with human preferences. It is a continuous process to keep the fine-tuned model accurate and effective in changing environments, to adapt to the data distribution shift (concept drift) and prevent performance degradation … Read more