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

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 and preferences—all while providing scalability and […]

Fast-track SOP processing using Amazon Bedrock

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), and a detailed approval and revision […]

Deploy Amazon SageMaker Projects with Terraform Cloud

Amazon SageMaker Projects empower data scientists to self-serve Amazon Web Services (AWS) tooling and infrastructure to organize all entities of the machine learning (ML) lifecycle, and further enable organizations to standardize and constrain the resources available to their data science teams in pre-packaged templates. For AWS customers using Terraform to define and manage their infrastructure-as-code (IaC), […]

Going beyond AI assistants: Examples from Amazon.com reinventing industries with generative AI

Generative AI revolutionizes business operations through various applications, including conversational assistants such as Amazon’s Rufus and Amazon Seller Assistant. Additionally, some of the most impactful generative AI applications operate autonomously behind the scenes, an essential capability that empowers enterprises to transform their operations, data processing, and content creation at scale. These non-conversational implementations, often in […]

Architect a mature generative AI foundation on AWS

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) and workflows involving agents. Safety controls […]

Using Amazon OpenSearch ML connector APIs

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 want to identify the language they […]

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

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 is a fully managed service that […]

Revolutionizing earth observation with geospatial foundation models on AWS

Emerging transformer-based vision models for geospatial data—also called geospatial foundation models (GeoFMs)—offer a new and powerful technology for mapping the earth’s surface at a continental scale, providing stakeholders with the tooling to detect and monitor surface-level ecosystem conditions such as forest degradation, natural disaster impact, crop yield, and many others. GeoFMs represent an emerging research […]

Create an agentic RAG application for advanced knowledge discovery with LlamaIndex, and Mistral in Amazon Bedrock

Agentic Retrieval Augmented Generation (RAG) applications represent an advanced approach in AI that integrates foundation models (FMs) with external knowledge retrieval and autonomous agent capabilities. These systems dynamically access and process information, break down complex tasks, use external tools, apply reasoning, and adapt to various contexts. They go beyond simple question answering by performing multi-step […]