Enhancing LLM Capabilities with NeMo Guardrails on Amazon SageMaker JumpStart

As large language models (LLMs) become increasingly integrated into customer-facing applications, organizations are exploring ways to leverage their natural language processing capabilities. Many businesses are investigating how AI can enhance customer engagement and service delivery, and facing challenges in making sure LLMs driven engagements are on topic and follow the desired instructions. In this blog … Read more

Build a multi-interface AI assistant using Amazon Q and Slack with Amazon CloudFront clickable references from an Amazon S3 bucket

There is consistent customer feedback that AI assistants are the most useful when users can interface with them within the productivity tools they already use on a daily basis, to avoid switching applications and context. Web applications like Amazon Q Business and Slack have become essential environments for modern AI assistant deployment. This post explores … Read more

Orchestrate seamless business systems integrations using Amazon Bedrock Agents

Generative AI has revolutionized technology through generating content and solving complex problems. To fully take advantage of this potential, seamless integration with existing business systems and efficient access to data are crucial. Amazon Bedrock Agents provides the integration capabilities to connect generative AI models with the wealth of information and workflows already in place within … Read more

Accelerate video Q&A workflows using Amazon Bedrock Knowledge Bases, Amazon Transcribe, and thoughtful UX design

Organizations are often inundated with video and audio content that contains valuable insights. However, extracting those insights efficiently and with high accuracy remains a challenge. This post explores an innovative solution to accelerate video and audio review workflows through a thoughtfully designed user experience that enables human and AI collaboration. By approaching the problem from … Read more

Boost team innovation, productivity, and knowledge sharing with Amazon Q Apps

As enterprises rapidly expand their applications, platforms, and infrastructure, it becomes increasingly challenging to keep up with technology trends, best practices, and programming standards. Enterprises typically provide their developers, engineers, and architects with a variety of knowledge resources such as user guides, technical wikis, code repositories, and specialized tools. However, over time these resources often … Read more

Harnessing Amazon Bedrock generative AI for resilient supply chain

From pandemic shutdowns to geopolitical tensions, recent years have thrown our global supply chains into unexpected chaos. This turbulent period has taught both governments and organizations a crucial lesson: supply chain excellence depends not just on efficiency but on the ability to navigate disruptions through strategic risk management. By leveraging the generative AI capabilities and … Read more

How Travelers Insurance classified emails with Amazon Bedrock and prompt engineering

This is a guest blog post co-written with Jordan Knight, Sara Reynolds, George Lee from Travelers. Foundation models (FMs) are used in many ways and perform well on tasks including text generation, text summarization, and question answering. Increasingly, FMs are completing tasks that were previously solved by supervised learning, which is a subset of machine … Read more

Accelerate digital pathology slide annotation workflows on AWS using H-optimus-0

Digital pathology is essential for the diagnosis and treatment of cancer, playing a critical role in healthcare delivery and pharmaceutical research and development. Pathology traditionally relies heavily on pathologist expertise and experience to conduct meticulous examination of tissue samples to identify abnormalities. However, the increasing complexity and volume of cases necessitate advanced tools to assist … Read more

DeepSeek-R1 model now available in Amazon Bedrock Marketplace and Amazon SageMaker JumpStart

Today, we are announcing that DeepSeek AI’s first-generation frontier model, DeepSeek-R1, is available through Amazon SageMaker JumpStart and Amazon Bedrock Marketplace to deploy for inference. You can now use DeepSeek-R1 to build, experiment, and responsibly scale your generative AI ideas on AWS. In this post, we demonstrate how to get started with DeepSeek-R1 on Amazon … Read more

Streamline grant proposal reviews using Amazon Bedrock

Government and non-profit organizations evaluating grant proposals face a significant challenge: sifting through hundreds of detailed submissions, each with unique merits, to identify the most promising initiatives. This arduous, time-consuming process is typically the first step in the grant management process, which is critical to driving meaningful social impact. The AWS Social Responsibility & Impact … Read more

How Aetion is using generative AI and Amazon Bedrock to unlock hidden insights about patient populations

The real-world data collected and derived from patient journeys offers a wealth of insights into patient characteristics and outcomes and the effectiveness and safety of medical innovations. Researchers ask questions about patient populations in the form of structured queries; however, without the right choice of structured query and deep familiarity with complex real-world patient datasets, … Read more

Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

Open foundation models (FMs) have become a cornerstone of generative AI innovation, enabling organizations to build and customize AI applications while maintaining control over their costs and deployment strategies. By providing high-quality, openly available models, the AI community fosters rapid iteration, knowledge sharing, and cost-effective solutions that benefit both developers and end-users. DeepSeek AI, a … Read more

Generative AI operating models in enterprise organizations with Amazon Bedrock

Generative AI can revolutionize organizations by enabling the creation of innovative applications that offer enhanced customer and employee experiences. Intelligent document processing, translation and summarization, flexible and insightful responses for customer support agents, personalized marketing content, and image and code generation are a few use cases using generative AI that organizations are rolling out in … Read more

Develop a RAG-based application using Amazon Aurora with Amazon Kendra

Generative AI and large language models (LLMs) are revolutionizing organizations across diverse sectors to enhance customer experience, which traditionally would take years to make progress. Every organization has data stored in data stores, either on premises or in cloud providers. You can embrace generative AI and enhance customer experience by converting your existing data into … Read more

Optimizing AI responsiveness: A practical guide to Amazon Bedrock latency-optimized inference

In production generative AI applications, responsiveness is just as important as the intelligence behind the model. Whether it’s customer service teams handling time-sensitive inquiries or developers needing instant code suggestions, every second of delay, known as latency, can have a significant impact. As businesses increasingly use large language models (LLMs) for these critical tasks and … Read more

Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

Evaluating large language models (LLMs) is crucial as LLM-based systems become increasingly powerful and relevant in our society. Rigorous testing allows us to understand an LLM’s capabilities, limitations, and potential biases, and provide actionable feedback to identify and mitigate risk. Furthermore, evaluation processes are important not only for LLMs, but are becoming essential for assessing … Read more

Create a SageMaker inference endpoint with custom model & extended container

Amazon SageMaker provides a seamless experience for building, training, and deploying machine learning (ML) models at scale. Although SageMaker offers a wide range of built-in algorithms and pre-trained models through Amazon SageMaker JumpStart, there are scenarios where you might need to bring your own custom model or use specific software dependencies not available in SageMaker … Read more

Image and video prompt engineering for Amazon Nova Canvas and Amazon Nova Reel

Amazon has introduced two new creative content generation models on Amazon Bedrock: Amazon Nova Canvas for image generation and Amazon Nova Reel for video creation. These models transform text and image inputs into custom visuals, opening up creative opportunities for both professional and personal projects. Nova Canvas, a state-of-the-art image generation model, creates professional-grade images … Read more

Security best practices to consider while fine-tuning models in Amazon Bedrock

Amazon Bedrock has emerged as the preferred choice for tens of thousands of customers seeking to build their generative AI strategy. It offers a straightforward, fast, and secure way to develop advanced generative AI applications and experiences to drive innovation. With the comprehensive capabilities of Amazon Bedrock, you have access to a diverse range of … Read more

Secure a generative AI assistant with OWASP Top 10 mitigation

A common use case with generative AI that we usually see customers evaluate for a production use case is a generative AI-powered assistant. However, before it can be deployed, there is the typical production readiness assessment that includes concerns such as understanding the security posture, monitoring and logging, cost tracking, resilience, and more. The highest … Read more

Streamline custom environment provisioning for Amazon SageMaker Studio: An automated CI/CD pipeline approach

Attaching a custom Docker image to an Amazon SageMaker Studio domain involves several steps. First, you need to build and push the image to Amazon Elastic Container Registry (Amazon ECR). You also need to make sure that the Amazon SageMaker domain execution role has the necessary permissions to pull the image from Amazon ECR. After … Read more

Enhance your customer’s omnichannel experience with Amazon Bedrock and Amazon Lex

The rise of AI has opened new avenues for enhancing customer experiences across multiple channels. Technologies like natural language understanding (NLU) are employed to discern customer intents, facilitating efficient self-service actions. Automatic speech recognition (ASR) translates spoken words into text, enabling seamless voice interactions. With Amazon Lex bots, businesses can use conversational AI to integrate … Read more

Introducing multi-turn conversation with an agent node for Amazon Bedrock Flows (preview)

Amazon Bedrock Flows offers an intuitive visual builder and a set of APIs to seamlessly link foundation models (FMs), Amazon Bedrock features, and AWS services to build and automate user-defined generative AI workflows at scale. Amazon Bedrock Agents offers a fully managed solution for creating, deploying, and scaling AI agents on AWS. With Flows, you … Read more

Video security analysis for privileged access management using generative AI and Amazon Bedrock

Security teams in highly regulated industries like financial services often employ Privileged Access Management (PAM) systems to secure, manage, and monitor the use of privileged access across their critical IT infrastructure. Security and compliance regulations require that security teams audit the actions performed by systems administrators using privileged credentials. Keystroke logging (the action of recording … Read more

How Cato Networks uses Amazon Bedrock to transform free text search into structured GraphQL queries

This is a guest post authored by Asaf Fried, Daniel Pienica, Sergey Volkovich from Cato Networks. Cato Networks is a leading provider of secure access service edge (SASE), an enterprise networking and security unified cloud-centered service that converges SD-WAN, a cloud network, and security service edge (SSE) functions, including firewall as a service (FWaaS), a … Read more

Solve forecasting challenges for the retail and CPG industry using Amazon SageMaker Canvas

Businesses today deal with a reality that is increasingly complex and volatile. Companies across retail, manufacturing, healthcare, and other sectors face pressing challenges in accurate planning and forecasting. Predicting future inventory needs, setting achievable strategic goals, and budgeting effectively involve grappling with ever-changing consumer demand and global market forces. Inventory shortages, surpluses, and unmet customer … Read more

Enabling generative AI self-service using Amazon Lex, Amazon Bedrock, and ServiceNow

Chat-based assistants have become an invaluable tool for providing automated customer service and support. This post builds on a previous post, Integrate QnABot on AWS with ServiceNow, and explores how to build an intelligent assistant using Amazon Lex, Amazon Bedrock Knowledge Bases, and a custom ServiceNow integration to create an automated incident management support experience. … Read more

How Kyndryl integrated ServiceNow and Amazon Q Business

This post is co-written with Sujith R Pillai from Kyndryl. In this post, we show you how Kyndryl, an AWS Premier Tier Services Partner and IT infrastructure services provider that designs, builds, manages, and modernizes complex, mission-critical information systems, integrated Amazon Q Business with ServiceNow in a few simple steps. You will learn how to … Read more

HCLTech’s AWS powered AutoWise Companion: A seamless experience for informed automotive buyer decisions with data-driven design

This post introduces HCLTech’s AutoWise Companion, a transformative generative AI solution designed to enhance customers’ vehicle purchasing journey. By tailoring recommendations based on individuals’ preferences, the solution guides customers toward the best vehicle model for them. Simultaneously, it empowers vehicle manufacturers (original equipment manufacturers (OEMs)) by using real customer feedback to drive strategic decisions, boosting … Read more

Mitigating risk: AWS backbone network traffic prediction using GraphStorm

The AWS global backbone network is the critical foundation enabling reliable and secure service delivery across AWS Regions. It connects our 34 launched Regions (with 108 Availability Zones), our more than 600 Amazon CloudFront POPs, and 41 Local Zones and 29 Wavelength Zones, providing high-performance, ultralow-latency connectivity for mission-critical services across 245 countries and territories. … Read more