Impel enhances automotive dealership customer experience with fine-tuned LLMs on Amazon SageMaker

Favorite This post is co-written with Tatia Tsmindashvili, Ana Kolkhidashvili, Guram Dentoshvili, Dachi Choladze from Impel. Impel transforms automotive retail through an AI-powered customer lifecycle management solution that drives dealership operations and customer interactions. Their core product, Sales AI, provides all-day personalized customer engagement, handling vehicle-specific questions and automotive trade-in

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Shared by AWS Machine Learning June 5, 2025

Build a scalable AI assistant to help refugees using AWS

Favorite This post is co-written with Taras Tsarenko, Vitalil Bozadzhy, and Vladyslav Horbatenko.  As organizations worldwide seek to use AI for social impact, the Danish humanitarian organization Bevar Ukraine has developed a comprehensive virtual generative AI-powered assistant called Victor, aimed at addressing the pressing needs of Ukrainian refugees integrating into

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Shared by AWS Machine Learning June 4, 2025

Unlocking the power of Model Context Protocol (MCP) on AWS

Favorite We’ve witnessed remarkable advances in model capabilities as generative AI companies have invested in developing their offerings. Language models such as Anthropic’s Claude Opus 4 & Sonnet 4 and Amazon Nova on Amazon Bedrock can reason, write, and generate responses with increasing sophistication. But even as these models grow

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Shared by AWS Machine Learning June 4, 2025

Fast-track SOP processing using Amazon Bedrock

Favorite Standard operating procedures (SOPs) are essential documents in the context of regulations and compliance. SOPs outline specific steps for various processes, making sure practices are consistent, efficient, and compliant with regulatory standards. SOP documents typically include key sections such as the title, scope, purpose, responsibilities, procedures, documentation, citations (references),

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Shared by AWS Machine Learning June 3, 2025

Streamline personalization development: How automated ML workflows accelerate Amazon Personalize implementation

Favorite Crafting unique, customized experiences that resonate with customers is a potent strategy for boosting engagement and fostering brand loyalty. However, creating dynamic personalized content is challenging and time-consuming because of the need for real-time data processing, complex algorithms for customer segmentation, and continuous optimization to adapt to shifting behaviors

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Shared by AWS Machine Learning June 3, 2025

Bridging the gap between development and production: Seamless model lifecycle management with Amazon Bedrock

Favorite In the landscape of generative AI, organizations are increasingly adopting a structured approach to deploy their AI applications, mirroring traditional software development practices. This approach typically involves separate development and production environments, each with its own AWS account, to create logical separation, enhance security, and streamline workflows. Amazon Bedrock

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Shared by AWS Machine Learning May 31, 2025

Using Amazon OpenSearch ML connector APIs

Favorite When ingesting data into Amazon OpenSearch, customers often need to augment data before putting it into their indexes. For instance, you might be ingesting log files with an IP address and want to get a geographic location for the IP address, or you might be ingesting customer comments and

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Shared by AWS Machine Learning May 31, 2025

Architect a mature generative AI foundation on AWS

Favorite Generative AI applications seem simple—invoke a foundation model (FM) with the right context to generate a response. In reality, it’s a much more complex system involving workflows that invoke FMs, tools, and APIs and that use domain-specific data to ground responses with patterns such as Retrieval Augmented Generation (RAG)

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Shared by AWS Machine Learning May 31, 2025