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 moreContinue Reading
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 courseContinue Reading
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.Continue Reading
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,Continue Reading
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 thisContinue Reading
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 largeContinue Reading
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 useContinue Reading
Organizations can optimize their migration and modernization projects by streamlining the containerization process for legacy applications. With the right tools and approaches, teams can transform traditional applications into containerized solutions efficiently, reducing the time spent on manual coding, testing, and debugging while enhancing developer productivity and accelerating time-to-market. During containerizationContinue Reading
IT teams face mounting challenges as they manage increasingly complex infrastructure and applications, often spending countless hours manually identifying operational issues, troubleshooting problems, and performing repetitive maintenance tasks. This operational burden diverts valuable technical resources from innovation and strategic initiatives. Artificial intelligence for IT operations (AIOps) presents a transformative solution,Continue Reading
Picture this: your machine learning (ML) team has a promising model to train and experiments to run for their generative AI project, but they’re waiting for GPU availability. The ML scientists spend time monitoring instance availability, coordinating with teammates over shared resources, and managing infrastructure allocation. Simultaneously, your infrastructure administratorsContinue Reading
