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

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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Transform AI development with new Amazon SageMaker AI model customization and large-scale training capabilities

Transform AI development with new Amazon SageMaker AI model customization and large-scale training capabilities

With the advancement in tools and services that make generative AI models accessible, businesses can now access the same foundation models (FMs) as their competitors. True differentiation comes from building AI that is highly customized for your business—something your competitors can’t effortlessly replicate. Although today’s FMs are genuinely intelligent with vast knowledge and reasoning capabilities, …

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Securing Amazon Bedrock cross-Region inference: Geographic and global

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 …

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

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 …

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Crossmodal search with Amazon Nova Multimodal Embeddings

Crossmodal search with Amazon Nova Multimodal Embeddings

Amazon Nova Multimodal Embeddings processes text, documents, images, video, and audio through a single model architecture. Available through Amazon Bedrock, the model converts different input modalities into numerical embeddings within the same vector space, supporting direct similarity calculations regardless of content type. We developed this unified model to reduce the need for separate embedding models, …

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Accelerating LLM inference with post-training weight and activation using AWQ and GPTQ on Amazon SageMaker AI

Accelerating LLM inference with post-training weight and activation using AWQ and GPTQ on Amazon SageMaker AI

Foundation models (FMs) and large language models (LLMs) have been rapidly scaling, often doubling in parameter count within months, leading to significant improvements in language understanding and generative capabilities. This rapid growth comes with steep costs: inference now requires enormous memory capacity, high-performance GPUs, and substantial energy consumption. This trend is evident in the open …

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How Beekeeper optimized user personalization with Amazon Bedrock

How Beekeeper optimized user personalization with Amazon Bedrock

This post is cowritten by Mike Koźmiński from Beekeeper. Large Language Models (LLMs) are evolving rapidly, making it difficult for organizations to select the best model for each specific use case, optimize prompts for quality and cost, adapt to changing model capabilities, and personalize responses for different users. Choosing the “right” LLM and prompt isn’t …

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