When you fine-tune a model using Supervised Fine-Tuning (SFT), creating high-quality chain-of-thought (CoT) reasoning traces for your training data is often impractical and can be prohibitively expensive. As a result, you might choose to skip reasoning during SFT and train with only inputs and outputs. However, reasoning is a key capability of the Amazon Nova … Read more
With the stock firmware and software, developers couldn’t modify their AWS DeepRacer devices to use the latest operating systems. Now, developers can upgrade or install a custom operating system (OS) by using a newly released bootloader, which extends the life of these hardware devices. AWS DeepRacer devices are fully autonomous 1/18th scale race cars driven … Read more
Fast-growing companies and enterprise supply-chain teams often have enough data to see that something is wrong, but not enough time to manually investigate every disruption. A supplier delay can require a planner to check purchase orders, inventory, customer commitments, contract rules, logistics options, and approval policies before deciding what to do next. Dashboards help teams … Read more
This post is co-written with Tushar Madaan from Couchbase. Building an AI-powered developer assistant that can generate database queries, recommend indexes, and support multi-turn conversational workflows requires more than a single large language model (LLM). It demands an inference architecture that is flexible, scalable, and resilient. As enterprise adoption of Capella iQ grew, Couchbase expanded … Read more
This guest post is co-written by Raphael Bres, Robert Iordache, Anca Andone, Ioana Millon (Ploesteanu) of Tradeshift and Roy Yung of AWS Tradeshift is an AI-powered accounts payable (AP) and e-Invoicing compliance platform serving buyers and sellers in more than 70 countries, with a cloud-based network that processes millions of transactions. We serve both sides … Read more
The average sales rep spends only 40% of their time actually selling. The rest is eaten up by necessary, but lower-value work: customer relationship management (CRM) updates, prospect research, email drafting, and endless context-switching between tools. Before you know it, the day has passed and you’ve spent only a small fraction of your time on … Read more
Teams that rely on dashboards for daily decisions often must pinch and zoom to interact with controls originally designed for larger displays. Checking revenue during a morning standup, reviewing pipeline metrics between meetings, or monitoring operations while traveling all require extra effort when the dashboard was built for a desktop screen. Mobile Layout for Amazon … Read more
Smartsheet is an enterprise work management platform that hundreds of thousands of organizations rely on. As enterprise teams adopt AI agents, those agents need structured access to the data inside systems like Smartsheet, but most systems aren’t built for that. To bridge this gap, Smartsheet built a remote Model Context Protocol (MCP) server on AWS … Read more
Knowledge bases that ground agents and generative AI applications over your enterprise data are hard to build at scale. Teams typically stitch together connectors, parsers, vector stores, knowledge graphs, and retrieval logic, then operationalize all of it for production. Each piece brings its own challenges. You must decide which data sources to connect and how … Read more
This post is co-written with Eric Jiang from xAI (SpaceXAI). xAI’s Grok 4.3 is now generally available on Amazon Bedrock, giving teams that build agents and AI workflows a model that reasons reliably over long inputs. With this launch, xAI joins Amazon Bedrock as a model provider. Grok 4.3 is a model with configurable reasoning … Read more
Restaurants miss an average of 150 phone calls per location every month, and about 60 percent of those are customers trying to place an order or book a table. Most of these calls come in during dinner service, exactly when the host is seating guests, servers are turning tables, and the phone becomes an afterthought. … Read more
Document processing in real estate is complex and highly manual, impacting critical business decisions at scale, making it ripe for automation. Built Technologies, a real estate finance software provider, processes over $500B in real estate projects. The company deployed an AI-powered document processing engine on Amazon Bedrock and the AWS Intelligent Document Processing (IDP) Accelerator. … Read more
The integration of AI into real-world applications has long been hindered by a fundamental challenge: the disconnect between systems that can see, systems that can think, and systems that can act. Developers have struggled with complex integrations, managing multiple APIs, and creating custom solutions to bridge these gaps, resulting in inefficient, costly, and often fragile … Read more
Using Amazon SageMaker Pipelines, organizations can automate their machine learning (ML) workloads and distribute them over many AWS accounts and AWS Regions as part of their Machine Learning Operations (MLOps) strategy. However, monitoring SageMaker Pipelines can become complex when they are distributed across many AWS environments. Developers and operations engineers must manually switch between multiple … Read more
Your prospects leave trails across multiple sources: a founder asks “What should I use for X?” in r/SaaS while their product launches on Hacker News. Stack Overflow questions spike. A GitHub repo crosses 2,400 stars. Each signal alone is noise, but correlated across sources, they reveal a prospect ready to buy. Multi-agent systems built with … Read more
Production quality assurance (QA) workflows require more than individual test execution. You must organize tests into regression suites that run as a batch, and integrate them into continuous integration and continuous delivery (CI/CD) pipelines so that test results gate deployments automatically. In a previous post, we introduced QA Studio, a reference solution for agentic QA … Read more
User experience (UX) testing faces multiple challenges that limit an organization’s ability to improve how users interact with their platforms. UX testing evaluates how easily and effectively users can navigate digital interfaces to complete intended tasks, such as finding products, creating accounts, or completing purchases. Unlike traditional Quality Assurance (QA) testing that focuses on functional … Read more
This post was written by Konstantin Lekh, Sasha Zinchuk, and Eugene Sergueev from Flo Health, and Liza (Elizaveta) Zinovyeva from AWS. In this post, we share how Flo Health’s engineering team turned a proof of concept (PoC) from the AWS Generative AI Innovation Center into a production-grade, AI-powered medical content review and generation system built … Read more
Healthcare organizations need efficient scheduling solutions, and ScienceSoft’s AI voice assistant, powered by Amazon Nova Sonic and Amazon Bedrock Guardrails, shows how responsible AI can deliver that. The AI patient scheduling software market is one of healthcare’s fastest-growing technology segments. According to Grand View Research, this market is growing rapidly, valued at approximately $260 million … Read more
Build with the smartest family of models from OpenAI yet, on Amazon Bedrock’s next-generation inference engine. Organizations scaling autonomous agents and AI-powered products need frontier intelligence that performs reliably across hundreds of steps, from coding agents shipping production code to cyber security research probing novel attack surfaces to genomics workflows analyzing entire gene sequences end-to-end. … Read more
AI as accessibility: what happened when a neurodivergent solutions architect stopped fighting his brain and started building. In this post, I share how AI serves as an accessibility tool for neurodivergent professionals. The system is built on Amazon Quick on your desktop, an AI-powered desktop and web assistant that compensates for executive function gaps every … Read more
This post is co-written with Vijay Venkatesh, CTO at Bluesight. If you build software for hospitals, you know that compliance work scales poorly. Hospitals managing 340B Drug Pricing Program compliance face a compounding data problem. Proving that a Group Purchasing Organization (GPO) purchased drug qualifies for an exception requires cross-referencing each purchase against several sources … Read more
When you deploy generative AI agents into multi-tenant production architectures, you face a specific identity problem: when an agent calls a downstream API on behalf of a user, whose identity travels with the call? Running the call as the agent’s service identity collapses the audit trail, because every downstream system must trust the agent unconditionally. … Read more
Deploying generative AI models to production requires finding the right combination of instance type, serving container with settings, and optimization strategy. This process typically requires a long iteration cycle of optimization and manual benchmarking. In April 2026, Amazon SageMaker AI launched this inference recommendations, so customers can programmatically get data-driven, production-ready configurations through APIs. This … Read more
Model customization transforms general-purpose AI models into specialized enterprise assets. By fine-tuning foundation models (FMs) on domain-specific data, businesses teach AI their unique workflows, terminology, and deep domain specialization, along with strict adherence to brand voice and fewer hallucinations. For enterprises, this is more than an optimization. It’s the creation of proprietary intellectual property. A … Read more
In dentistry, image quality determines whether a claim is paid or denied. Up to 20 percent insurance claims are initially denied, with missing or low-quality images among the leading causes. Yet quality assessment has traditionally been a manual, after-the-fact process. A clinician reviews an X-ray hours or days after capture, discovering problems only when a … Read more
In this post we show how to build a semantic layer on AWS using Stardog’s Semantic AI Application over Amazon Aurora and Amazon Redshift, and how to run a Strands Agents agent on Amazon Bedrock AgentCore that queries the layer to answer customer 360 questions across both sources without extract, transform, and load (ETL). The … Read more
An artificial intelligence (AI) agent can process an invoice, help adjudicate a claim, or classify a support ticket in a proof of concept. But running these agents across thousands or even millions of work items in a production environment introduces an entirely different set of challenges. At enterprise scale, success depends on much more than … Read more
This post was co-written with Daniel Han and Michael Han from Unsloth. Deploying large foundation models (FMs) stored at their original 16-bit floating-point precision (BF16 or FP16) is expensive. They need large GPU instances, driving up serving costs, and slowing down iteration cycles. Quantization addresses this by reducing the numerical precision of a model’s weights … Read more
When Model Context Protocol (MCP) tools underperform, the cause is rarely the protocol itself but the tool design. Many teams start by exposing an existing API as-is and trusting the agent to figure out the rest. It is a natural way to extend APIs to agentic systems and generative AI coding tools. For straightforward use … Read more