engblogs

Outlines the 2026 strategic priorities for data and AI leaders, emphasizing unified, governed data estates, interoperable AI workloads and agents, flexible LLM selection, and governance as the foundation for scalable, reliable enterprise AI.

Agentforce-powered, AI-driven multi-agent incident response within Salesforce's Centralized Incident Response reduces Severity 2 resolution time by 70-80% through automated detection, hypothesis generation, and runbook execution.

Build an AI-powered website assistant with Amazon Bedrock to deliver instant, relevant answers via knowledge bases and retrieval-augmented generation, powered by a serverless, CI/CD deployed architecture.

Migrate a self-managed MLflow tracking server to a serverless MLflow App on Amazon SageMaker AI, using the MLflow Export Import tool to transfer experiments, runs, models, and metadata with automatic scaling and reduced maintenance.

Leverage BentoML’s LLM-Optimizer to automate the benchmarking and tuning of large language model inference parameters for optimized deployment on Amazon SageMaker AI, balancing latency, throughput, and cost effectively.

Explore how agentic AI enhances QA automation with Amazon Bedrock AgentCore Browser and Amazon Nova Act, enabling autonomous, scalable, and parallel UI testing for modern applications.

Artificial intelligence agents enable scalable, adaptive browser automation to streamline complex enterprise workflows like e-commerce order processing, reducing manual effort and improving compliance.

Leverage Amazon Bedrock Data Automation, Strands SDK, and AgentCore to programmatically build an intelligent document processing solution that extracts insights from multi-modal business documents using Retrieval-Augmented Generation workflows.

Exploring the history and sociopolitical factors behind the emergence of standardized spelling rules across different languages.

Visa Intelligent Commerce on AWS leverages Amazon Bedrock AgentCore to enable secure, scalable, multi-agent AI systems that automate agentic commerce workflows for travel and shopping through natural language commands and tokenized payments.

Leverage Amazon Nova foundation models to automate and accelerate marketing campaign ideation and visual asset generation, enhancing efficiency, consistency, and creativity through generative AI-powered tools and serverless architecture.

Qbtech leveraged Amazon SageMaker AI and AWS Glue to develop and deploy a clinically validated mobile AI model that streamlines ADHD diagnosis by processing multimodal smartphone sensor data with 96% faster feature engineering and enabling accessible, objective assessment from patients' devices.