Machine Learning

Organizations are increasingly excited about the potential of AI agents, but many find themselves stuck in what we call “proof of concept purgatory”—where promising agent prototypes struggle to make the leap to production deployment. In our conversations with customers, we’ve heard consistent challenges that block the path from experimentation to enterprise-grade deployment: “Our developers want … Read more

This is a guest post co-written with Scott Likens, Ambuj Gupta, Adam Hood, Chantal Hudson, Priyanka Mukhopadhyay, Deniz Konak Ozturk, and Kevin Paul from PwC Organizations are deploying generative AI solutions while balancing accuracy, security, and compliance. In this globally competitive environment, scale matters less, speed matters more, and innovation matters most of all, according … Read more

At Amazon, our team builds Rufus, a generative AI-powered shopping assistant that serves millions of customers at immense scale. However, deploying Rufus at scale introduces significant challenges that must be carefully navigated. Rufus is powered by a custom-built large language model (LLM). As the model’s complexity increased, we prioritized developing scalable multi-node inference capabilities that … Read more

Agentic AI is revolutionizing the financial services industry through its ability to make autonomous decisions and adapt in real time, moving well beyond traditional automation. Imagine an AI assistant that can analyze quarterly earnings reports, compare them against industry expectations, and generate insights about future performance. This seemingly straightforward task involves multiple complex steps: document … Read more

AI assistants that forget what you told them 5 minutes ago aren’t very helpful. While large language models (LLMs) excel at generating human-like responses, they are fundamentally stateless—they don’t retain information between interactions. This forces developers to build custom memory systems to track conversation history, remember user preferences, and maintain context across sessions, often solving … Read more

Data analysis often presents significant challenges for business users who aren’t proficient in SQL. Traditional methods require technical expertise to query databases, leading to delayed insights and dependence on data teams. Many organizations struggle with making their data accessible to business users while maintaining the analytical capabilities of Amazon Athena. Modern AI agents are transforming … Read more

Imagine harnessing the power of 72 cutting-edge NVIDIA Blackwell GPUs in a single system for the next wave of AI innovation, unlocking 360 petaflops of dense 8-bit floating point (FP8) compute and 1.4 exaflops of sparse 4-bit floating point (FP4) compute. Today, that’s exactly what Amazon SageMaker HyperPod delivers with the launch of support for … Read more

This post is co-written with Rudra Kannemadugu and Shravan K S from Indegene Limited. In today’s digital-first world, healthcare conversations are increasingly happening online. Yet the life sciences industry has struggled to keep pace with this shift, facing challenges in effectively analyzing and deriving insights from complex medical discussions on a scale. This post will … Read more

This post is co-authored with Karsten Weber and Rosary Wang from Lexbe. Legal professionals are frequently tasked with sifting through vast volumes of documents to identify critical evidence for litigation. This process can be time-consuming, prone to human error, and expensive—especially when tight deadlines loom. Lexbe, a leader in legal document review software, confronted these … Read more

In Part 1 of our series, we established the architectural foundation for an enterprise artificial intelligence and machine learning (AI/ML) configuration with Amazon SageMaker Unified Studio projects. We explored the multi-account structure, project organization, multi-tenancy approaches, and repository strategies needed to create a governed AI development environment. In this post, we focus on implementing this … Read more

Amazon SageMaker Unified Studio represents the evolution towards unifying the entire data, analytics, and artificial intelligence and machine learning (AI/ML) lifecycle within a single, governed environment. As organizations adopt SageMaker Unified Studio to unify their data, analytics, and AI workflows, they encounter new challenges around scaling, automation, isolation, multi-tenancy, and continuous integration and delivery (CI/CD). … Read more

“How much will it cost to run our chatbot on Amazon Bedrock?” This is one of the most frequent questions we hear from customers exploring AI solutions. And it’s no wonder — calculating costs for AI applications can feel like navigating a complex maze of tokens, embeddings, and various pricing models. Whether you’re a solution … Read more

Released on August 5, 2025, OpenAI’s GPT-OSS models, gpt-oss-20b and gpt-oss-120b, are now available on AWS through Amazon SageMaker AI and Amazon Bedrock. These pre-trained, text-only Transformer models are built on a Mixture-of-Experts (MoE) architecture that activates only a subset of parameters per token, delivering high reasoning performance while reducing compute costs. They specialize in … Read more

DTDC is India’s leading integrated express logistics provider, operating the largest network of customer access points in the country. DTDC’s technology-driven logistics solutions cater to a wide range of customers across diverse industry verticals, making them a trusted partner in delivering excellence. DTDC Express Limited receives over 400,000 customer queries each month, ranging from tracking … Read more

AI agents are rapidly transforming enterprise operations. Although a single agent can perform specific tasks effectively, complex business processes often span multiple systems, requiring data retrieval, analysis, decision-making, and action execution across different systems. With multi-agent collaboration, specialized AI agents can work together to automate intricate workflows. This post explores a practical collaboration, integrating Salesforce … Read more

At AWS, our sales teams create customer-focused documents called account plans to deeply understand each AWS customer’s unique goals and challenges, helping account teams provide tailored guidance and support that accelerates customer success on AWS. As our business has expanded, the account planning process has become more intricate, requiring detailed analysis, reviews, and cross-team alignment … Read more

Organizations today face a critical challenge: managing an ever-increasing volume of tasks and information across multiple systems. Although traditional task management tools help organize work, they often fall short in delivering the intelligence needed for truly efficient operations. Today, we’re excited to announce the integration of Asana AI Studio with Amazon Q index, bringing generative … Read more

The payments industry stands at the forefront of digital transformation, with artificial intelligence (AI) rapidly becoming a cornerstone technology that powers a variety of solutions, from fraud detection to customer service. According to the following Number Analytics report, digital payment transactions are projected to exceed $15 trillion globally by 2027. Generative AI has expanded the … Read more

In Part 1 of our series, we explored the foundational concepts of responsible AI in the payments industry. In this post, we discuss the practical implementation of responsible AI frameworks. The need for responsible AI The implementation of responsible AI is not passive, but a dynamic process of reimagining how technology can serve a customer’s … Read more

Organizations across industries face challenges with high volumes of multi-page documents that require intelligent processing to extract accurate information. Although automation has improved this process, human expertise is still needed in specific scenarios to verify data accuracy and quality. In March 2025, AWS launched Amazon Bedrock Data Automation, which enables developers to automate the generation … Read more

Organizations need user-friendly ways to build AI assistants that can reference enterprise documents while maintaining document security. This post shows how to use Amazon Q Business to create an AI assistant that provides clickable URLs to source documents stored in Amazon Simple Storage Service (Amazon S3), to support secure document access and verification. Amazon Q … Read more

Today, we are excited to announce the availability of Open AI’s new open weight GPT OSS models, gpt-oss-120b and gpt-oss-20b, from OpenAI in Amazon SageMaker JumpStart. With this launch, you can now deploy OpenAI’s newest reasoning models to build, experiment, and responsibly scale your generative AI ideas on AWS. In this post, we demonstrate how … Read more

Amazon Q Business is a fully managed, generative AI-powered assistant that helps enterprises unlock the value of their data and knowledge. With Amazon Q Business, you can quickly find answers to questions, generate summaries and content, and complete tasks by using the information and expertise stored across your company’s various data sources and enterprise systems. … Read more

Picture this: Your team just received 10,000 customer feedback responses. The traditional approach? Weeks of manual analysis. But what if AI could not only analyze this feedback but also validate its own work? Welcome to the world of large language model (LLM) jury systems deployed using Amazon Bedrock. As more organizations embrace generative AI, particularly … Read more

The education sector needs efficient, high-quality course material development that can keep pace with rapidly evolving knowledge domains. Faculty invest days to create content and quizzes for topics to be taught in weeks. Increased faculty engagement in manual content creation creates a time deficit for innovation in teaching, inconsistent course material, and a poor experience … Read more

Handmade.com is a leading hand-crafts product marketplace, offering unique, seller-contributed items to customers around the world. With over 60,000 products in the catalog and some percentage of listings containing basic descriptions that could be improved for better search and search engine optimization (SEO) performance, the need for automation became evident. Manual processing, consuming on average … Read more

Organizations serving multiple tenants through AI applications face a common challenge: how to track, analyze, and optimize model usage across different customer segments. Although Amazon Bedrock provides powerful foundation models (FMs) through its Converse API, the true business value emerges when you can connect model interactions to specific tenants, users, and use cases. Using the … Read more

At AWS Summit New York City 2025, Amazon Web Services (AWS) announced the preview of Amazon Bedrock AgentCore browser tool, a fully managed, pre-built cloud-based browser. This tool enables generative AI agents to interact seamlessly with websites. It addresses two fundamental limitations: first, foundation models (FMs) are trained on large but static datasets and need … Read more

AI agents have reached a critical inflection point where their ability to generate sophisticated code exceeds the capacity to execute it safely in production environments. Organizations deploying agentic AI face a fundamental dilemma: although large language models (LLMs) can produce complex code scripts, mathematical analyses, and data visualizations, executing this AI-generated code introduces significant security … Read more

This post is co-written with Rich Young from Arize AI. Agentic AI applications built on agentic workflows differ from traditional workloads in one important way: they’re nondeterministic. That is, they can produce different results with the same input. This is because the large language models (LLMs) they’re based on use probabilities when generating each token. … Read more