In this post, we explore how natural language database analytics can revolutionize the way organizations interact with their structured data through the power of large language model (LLM) agents. Natural language interfaces to databases have long been a goal in data management. Agents enhance...
This post was co-written with Nick Frichette and Vijay George from Datadog.
As organizations increasingly adopt Amazon Bedrock for generative AI applications, protecting against misconfigurations that could lead to data leaks or unauthorized model access becomes critical. The AWS Generative AI Adoption Index, which surveyed...
When deploying AI agents to Amazon Bedrock AgentCore Runtime (currently in preview), customers often want to use custom domain names to create a professional and seamless experience.
By default, AgentCore Runtime agents use endpoints like https://bedrock-agentcore.{region}.amazonaws.com/runtimes/{EncodedAgentARN}/invocations.
In this post, we discuss how to transform these endpoints...
Today, we’re excited to announce that Amazon SageMaker HyperPod now supports managed node automatic scaling with Karpenter, so you can efficiently scale your SageMaker HyperPod clusters to meet your inference and training demands. Real-time inference workloads require automatic scaling to address unpredictable traffic patterns...
Finance analysts across Amazon Finance face mounting complexity in financial planning and analysis processes. When working with vast datasets spanning multiple systems, data lakes, and business units, analysts encounter several critical challenges. First, they spend significant time manually browsing data catalogs and reconciling data...
Air pollution remains one of Africa’s most pressing environmental health crises, causing widespread illness across the continent. Organizations like sensors.AFRICA have deployed hundreds of air quality sensors to address this challenge, but face a critical data problem: significant gaps in PM2.5 (particulate matter with...
