Worldwide Express (part of ShipStation Global) had built something big: approximately $5 billion in systemwide revenue, over 75 less-than-truckload (LTL) carriers and more than 130,000 customers. But that same scale had a hidden cost. Every month, $15 million in free cash flow sat frozen, locked in billing exceptions no one had resolved yet. Each one … Read more
The ChatGPT desktop app is now available on Amazon Bedrock in AWS GovCloud (US), providing access to OpenAI’s frontier models through two components. Work completes complex, multi-step tasks and delivers review-ready results, and Codex is a coding agent for developing, testing, and reviewing software. This walkthrough is intended for organizations whose security architecture requires model … Read more
The Amazon Quick User Group – United Kingdom is a community of Amazon Quick users in the United Kingdom who meet quarterly to exchange knowledge, share best practices, learn through hands-on sessions, and discuss their experiences using the service. These user groups function as collaborative forums where members learn, connect, and innovate together. Whether you’re … Read more
To scale intent-driven UI testing across its product teams, Epsilon, a data, technology, and marketing-services company and part of Publicis Groupe, turned to Amazon Nova Act. With hundreds of millions of consumer profiles and thousands of brand relationships, Epsilon needed UI testing that could keep pace with rapid application changes. The solution could not create … Read more
When your team moves a mature PHP application to Java, you gain stronger type safety, broader library support, and more predictable scaling. A PHP codebase built over the years with Laravel, Symfony, or Doctrine carries business rules in places that are not obvious, from Eloquent traits to XML mapping files, so a structurally similar Java … Read more
With the launch of AWS Batch support for Amazon SageMaker Training jobs, customers gained a new fully managed way to queue, schedule, and retry machine learning (ML) training workloads without building their own infrastructure. Instead, they use the queuing and scheduling features of AWS Batch. As organizations scale their artificial intelligence and machine learning (AI/ML) … Read more
This post was co-written with Nikhil Kumar and Shakir Khan from MoEngage. When engineering teams start building AI agents, the capabilities those agents need usually already exist as internal APIs. Campaign creation, segment queries, delivery stats. The challenge isn’t building new functionality. The challenge is making hundreds of private APIs safely reachable by agents without … Read more
NVIDIA Nemotron 3.5 Super VL joins the NVIDIA Nemotron 3 Nano, Nano Omni, Super, Ultra, and Nemotron 3.5 Lightning models already available on AWS. It’s a 120B-parameter mixture-of-experts (MoE) model that activates 12B parameters per token. It combines reasoning and tool use with text, image, document, and video understanding, so one model serves both text … Read more
If you’ve tried to get an agent into production, the model and tool use are not the blocker. The main bottleneck is everything around them: how many teams can build within a secure environment, which team owns each model and tool, how AgentOps and error handling stay inside a pre-defined boundary, and how platform, Workstream, … Read more
What usually stops PyTorch training from scaling out to a cluster is the container, not the model code. Every container needs the same CUDA runtime, a PyTorch build compiled against it, NCCL (NVIDIA Collective Communications Library), the Elastic Fabric Adapter (EFA) userspace libraries, the AWS OFI NCCL plugin that connects NCCL to EFA, and a … Read more
As quality assurance (QA) automation adoption grows inside an organization, a new problem appears that has nothing to do with writing tests. A platform team stands up test automation, then a second team wants to join, then a dozen more. Soon hundreds of test cases belong to different products and squads, and everyone can see … Read more
I’m proud to share that Amazon Web Services (AWS) has been named a Leader in the 2026 Gartner Magic Quadrant for Contact Center as a Service (CCaaS) for Amazon Connect for the fourth consecutive year. We believe this recognition reflects years of work pushing on what’s possible in customer experience. When we launched Amazon Connect … Read more
Every minute your deep learning container image spends downloading is a minute you pay for and a minute your team waits. Container image download is pure overhead: billable job time that produces no model progress. For modern deep learning images, that overhead is several minutes on every single job. Today, we’re excited to announce Seekable … Read more
This post was co-authored with Khaled Thabit, Meriem Boughrara, and Mohamed Desouky from Property Finder. The engineering team at Property Finder, a digital real estate application, discovered that 96.8 percent of their evaluation labels had been inherited directly from a single model’s predictions rather than verified by human experts. Their ground truth was systematically skewed … Read more
Exowatt builds modular, dispatchable solar systems that deliver reliable power for energy-intensive applications such as AI data centers. Its flagship product, the Exowatt P3, captures solar energy through optical lenses, stores it as heat in a long-duration thermal battery, and dispatches electricity on demand through a heat engine. Unlike grid-tied photovoltaic solar systems, P3 powers … Read more
Fleet-wide computer vision model lifecycle management is a problem that shows up the moment a quality inspection proof of concept succeeds. One camera and one model work fine. Then the plant asks for the same result on 40 lines, each with several cameras, and every camera sees the world differently. Each has a different angle, … Read more
Every time you spin off your agent, it has to re-read its whole life story before performing an action. Here’s how to make it remember without having to feed it the same context again. In the movie Groundhog Day, Bill Murray’s character re-lives the same February 2 every day. He wakes up to the same … Read more
This post builds enterprise agentic retrieval on a Managed Amazon Bedrock Knowledge Base with the AWS Cloud Development Kit (AWS CDK). To see why that’s worth building, it helps to start with where ordinary Retrieval Augmented Generation (RAG) breaks down. Most RAG systems start the same way: they embed the question, fetch the nearest chunks … Read more
Most fine-tuning teaches a model to produce a better answer to a single prompt. Agentic tasks are different. An agent that files an expense report or triages a support ticket takes a sequence of actions, and each step depends on what came before. There’s rarely one correct sequence to imitate, and the only reliable feedback … Read more
Updating the Amazon Sagemaker AI real-time endpoint configuration (changing the instance type, instance count, or environment variables) causes deployments through AWS CloudFormation or the AWS Cloud Development Kit (AWS CDK) to fail. SageMaker AI requires you to deregister the scalable target before updating the endpoint, but when you deregister it, CloudFormation can’t track the AWS … Read more
With Amazon Quick Sight layer maps, you can now plot points and routes, like store locations across a city or flights leaving an airport. Geospatial maps help businesses spot patterns that are tied to location, like how a region is performing or where customers are concentrated. Amazon Quick Sight supports this with multiple map types, … Read more
Plant breeding decisions depend on data that spans genomics, field trials, imagery, environmental conditions, and model outputs. Bayer Crop Science runs hundreds of machine learning (ML) model configurations against this data across crops, regions, and teams, and each run needs to be repeatable and governed. To meet that requirement, Bayer built the Connected Decision Engine … Read more
Amazon Polly Generative engine now offers more natural and accurate speech output. We’re introducing an upgrade to the Amazon Polly Generative engine that delivers more expressive, more accurate speech output with low latency. The upgrade adds 14 new voices across 9 locales, including general availability of Generative voices in Hindi and Finnish for the first … Read more
IskayPet’s office teams had a knowledge challenge. Answers to everyday operational questions, such as a return policy, a veterinary protocol, or an onboarding step, lived in hundreds of Microsoft SharePoint documents spread across four languages and three countries. Finding the right information in large document repositories took a long time. Every new store, country, or … Read more
Companies getting real results from AI aren’t only using foundation models (FMs) off the shelf. They’re customizing open-weight models using post-training techniques such as reinforcement learning. A model trained on your business context, product catalog, or clinical vocabulary will be more accurate for your task and cost less to run. When you build agents, your … Read more
Fine-tuning a large language model (LLM) today usually forces a tradeoff between training loop control and operational simplicity. With fully managed services you select a base model, provide data and hyperparameters, and the service owns everything else, which works well when a standard, prepackaged recipe fits your problem. Less managed services give you more control, … Read more
Healthcare organizations want the same thing from AI that every other business wants: faster answers, less manual work, and insights that reach decision-makers in time to act on them. However, what makes the healthcare industry different is that the data is uniquely complex, deeply contextual, and strictly regulated. So this post starts with a few … Read more
A customer asks an AI voice agent a question and waits. The agent already has an answer, it’s midway through generating a long, multi-paragraph response, but the customer hears nothing for five seconds. By the time an answer arrives, the customer is frustrated, confused, and no longer paying attention. Text-to-speech integrations create exactly that gap. … Read more
A traffic spike hits your self-hosted text-to-speech (TTS) endpoint, and requests start queueing. Latency climbs past your service level objective (SLO) right when the most callers are listening. The auto scaling policy behind that endpoint was supposed to prevent this, but the target value it scales on was a guess, and guesses like that fail … Read more
Every engineering team knows the ritual, and Rescale was no exception. A nightly test suite fails. An on-call engineer pulls the logs, classifies the root cause, and routes it to the right team, only to repeat the process the next morning. At scale, across distributed services and dozens of repositories, this ritual becomes a full-time job … Read more