Plenitude built an agent-based system on Databricks Genie that converts unstructured PDFs for solar and wind maintenance into a unified, queryable data model, enabling natural-language questions and visualizations across plants.

AWS's cross-Region Inference (CRIS) on Amazon Bedrock helps European customers leverage model capacity across multiple AWS regions while adhering to GDPR and other data protection requirements. This post explores global and EU geographic inference profiles, security features, transparency tools, and how to check available profiles.

Amazon Bedrock AgentCore Runtime gives each agent session its own isolated microVM with a persistent workspace, secure tool access through Gateway, and built-in observability—so you can run Claude Code, Codex, Kiro, and Cursor in parallel without sharing secrets, ports, or filesystems. Close the lid, go to dinner, and pick up where you left off tomorrow.

This post introduces mathematical optimization as a subfield of AI, explains how it differs from machine learning, and showcases real-world success stories from the AWS Generative AI Innovation Center that deliver concrete business results.

This post demonstrates how to use Amazon SageMaker AI with fully homomorphic encryption (FHE) to run ML inference entirely in the encrypted domain. By leveraging the concrete-ml library (API-compatible with scikit-learn), you can train FHE models and deploy them to SageMaker endpoints, ensuring that queries, responses, and intermediate values remain encrypted and unreadable by any observer, including SageMaker itself. The article covers sensitive use cases in healthcare, energy, and telecommunications, and provides step-by-step implementation guidance.

This post introduces the Nova Sonic Test Harness, an open source framework that automatically runs multi-turn conversations, evaluates voice agent quality, and detects audio hallucinations. It enables rapid iteration on prompts and tool configuration, as well as comprehensive regression testing at scale.