Build a conversational data assistant, Part 1: Text-to-SQL with Amazon Bedrock Agents

What if you could replace hours of data analysis with a minute-long conversation? Large language models can transform how we bridge the gap between business questions and actionable data insights. For most organizations, this gap remains stubbornly wide, with business teams trapped in endless cycles—decoding metric definitions and hunting for the correct data sources to […]

Implement user-level access control for multi-tenant ML platforms on Amazon SageMaker AI

Managing access control in enterprise machine learning (ML) environments presents significant challenges, particularly when multiple teams share Amazon SageMaker AI resources within a single Amazon Web Services (AWS) account. Although Amazon SageMaker Studio provides user-level execution roles, this approach becomes unwieldy as organizations scale and team sizes grow. Refer to the Operating model whitepaper for […]

Long-running execution flows now supported in Amazon Bedrock Flows in public preview

Today, we announce the public preview of long-running execution (asynchronous) flow support within Amazon Bedrock Flows. With Amazon Bedrock Flows, you can link foundation models (FMs), Amazon Bedrock Prompt Management, Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, Amazon Bedrock Guardrails, and other AWS services together to build and scale predefined generative AI workflows. As customers […]

Fraud detection empowered by federated learning with the Flower framework on Amazon SageMaker AI

Fraud detection remains a significant challenge in the financial industry, requiring advanced machine learning (ML) techniques to detect fraudulent patterns while maintaining compliance with strict privacy regulations. Traditional ML models often rely on centralized data aggregation, which raises concerns about data security and regulatory constraints. Fraud cost businesses over $485.6 billion in 2023 alone, according […]

Building intelligent AI voice agents with Pipecat and Amazon Bedrock – Part 2

Voice AI is changing the way we use technology, allowing for more natural and intuitive conversations. Meanwhile, advanced AI agents can now understand complex questions and act autonomously on our behalf. In Part 1 of this series, you learned how you can use the combination of Amazon Bedrock and Pipecat, an open source framework for […]

Accelerate foundation model development with one-click observability in Amazon SageMaker HyperPod

Amazon SageMaker HyperPod now provides a comprehensive, out-of-the-box dashboard that delivers insights into foundation model (FM) development tasks and cluster resources. This unified observability solution automatically publishes key metrics to Amazon Managed Service for Prometheus and visualizes them in Amazon Managed Grafana dashboards, optimized specifically for FM development with deep coverage of hardware health, resource […]

Accelerating generative AI development with fully managed MLflow 3.0 on Amazon SageMaker AI

Amazon SageMaker now offers fully managed support for MLflow 3.0 that streamlines AI experimentation and accelerates your generative AI journey from idea to production. This release transforms managed MLflow from experiment tracking to providing end-to-end observability, reducing time-to-market for generative AI development. As customers across industries accelerate their generative AI development, they require capabilities to […]