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How the Amazon AMET Payments team accelerates test case generation with Strands Agents

At Amazon.ae, we serve approximately 10 million customers monthly across five countries in the Middle East and North Africa region—United Arab Emirates (UAE), Saudi Arabia, Egypt, Türkiye, and South Africa. Our AMET (Africa, Middle East, and Türkiye) Payments team manages payment selections, transactions, experiences, and affordability features across these diverse countries, publishing on average five …

Introducing BigQuery managed and SQL-native inference for open models

BigQuery provides access to a variety of LLMs for text and embedding generation, including Google’s Gemini models, Google-managed models from partners like Anthropic and Mistral. Using Gemini models and Google-managed partner models in BigQuery is simple — just create the model with the foundation model name and run inference directly in SQL queries. Today, we …

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How AutoScout24 built a Bot Factory to standardize AI agent development with Amazon Bedrock

AutoScout24 is Europe’s leading automotive marketplace platform that connects buyers and sellers of new and used cars, motorcycles, and commercial vehicles across several European countries. Their long-term vision is to build a Bot Factory, a centralized framework for creating and deploying artificial intelligence (AI) agents that can perform tasks and make decisions within workflows, to …

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Palo Alto Networks automates customer intelligence document creation with agentic design

For a global cybersecurity leader like Palo Alto Networks, a comprehensive understanding of each customer is critical for success. For every engagement the Palo Alto Networks pre-sales team has, the comprehensive understanding is centralized in an internal Document of Record (DOR), a vital asset that provides a 360-degree standardized view of the customer for sales …

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Securing Amazon Bedrock cross-Region inference: Geographic and global

The adoption and implementation of generative AI inference has increased with organizations building more operational workloads that use AI capabilities in production at scale. To help customers achieve the scale of their generative AI applications, Amazon Bedrock offers cross-Region inference (CRIS) profiles, a powerful feature organizations can use to seamlessly distribute inference processing across multiple …

A gRPC transport for the Model Context Protocol

AI agents are moving from test environments to the core of enterprise operations, where they must interact reliably with external tools and systems to execute complex, multi-step goals. The Model Context Protocol (MCP) is the standard that makes this agent to tool communication possible. In fact, just last month we announced the release of fully-managed, …

Over-Searching in Search-Augmented Large Language Models

Search-augmented large language models (LLMs) excel at knowledge-intensive tasks by integrating external retrieval. However, they often over-search – unnecessarily invoking search tool even when it does not improve response quality, which leads to computational inefficiency and hallucinations by incorporating irrelevant context. In this work, we conduct a systematic evaluation of over-searching across multiple dimensions, including …

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How Omada Health scaled patient care by fine-tuning Llama models on Amazon SageMaker AI

This post is co-written with Sunaina Kavi, AI/ML Product Manager at Omada Health. Omada Health, a longtime innovator in virtual healthcare delivery, launched a new nutrition experience in 2025, featuring OmadaSpark, an AI agent trained with robust clinical input that delivers real-time motivational interviewing and nutrition education. It was built on AWS. OmadaSpark was designed …

MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer

Unified multimodal Large Language Models (LLMs) that can both understand and generate visual content hold immense potential. However, existing open-source models often suffer from a performance trade-off between these capabilities. We present Manzano, a simple and scalable unified framework that substantially reduces this tension by coupling a hybrid image tokenizer with a well-curated training recipe. …