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This post is co-written by Instituto de Ciência e Tecnologia Itaú (ICTi) and AWS. Sentiment analysis has grown increasingly important in modern enterprises, providing insights into customer opinions, satisfaction levels, and potential frustrations. As interactions occur largely through text (such as social media, chat applications, and ecommerce reviews) or voice (such as call centers and …

Sentiment Analysis with Text and Audio Using AWS Generative AI Services: Approaches, Challenges, and Solutions Read More »

This post is co-written by TrueLook and AWS. TrueLook is a construction camera and jobsite intelligence company that provides real-time visibility into construction projects. Its platform combines high-resolution time-lapse cameras, live video streaming, and AI-powered insights to help teams monitor progress, improve accountability, and reduce risk across the entire project lifecycle. TrueLook used Amazon SageMaker …

Architecting TrueLook’s AI-powered construction safety system on Amazon SageMaker AI Read More »

This blog post is based on work co-developed with Flo Health. Healthcare science is rapidly advancing. Maintaining accurate and up-to-date medical content directly impacts people’s lives, health decisions, and well-being. When someone searches for health information, they are often at their most vulnerable, making accuracy not just important, but potentially life-saving. Flo Health creates thousands …

Scaling medical content review at Flo Health using Amazon Bedrock (Part 1) Read More »

Organizations handle vast amounts of sensitive customer information through various communication channels. Protecting Personally Identifiable Information (PII), such as social security numbers (SSNs), driver’s license numbers, and phone numbers has become increasingly critical for maintaining compliance with data privacy regulations and building customer trust. However, manually reviewing and redacting PII is time-consuming, error-prone, and scales …

Detect and redact personally identifiable information using Amazon Bedrock Data Automation and Guardrails Read More »

This post is cowritten with Aashraya Sachdeva from Observe.ai. You can use Amazon SageMaker to build, train and deploy machine learning (ML) models, including large language models (LLMs) and other foundation models (FMs). This helps you significantly reduce the time required for a range of generative AI and ML development tasks. An AI/ML development cycle …

Speed meets scale: Load testing SageMakerAI endpoints with Observe.AI’s testing tool Read More »

Here are Google’s latest AI updates from December 2025 ​ 

Operating a self-managed MLflow tracking server comes with administrative overhead, including server maintenance and resource scaling. As teams scale their ML experimentation, efficiently managing resources during peak usage and idle periods is a challenge. Organizations running MLflow on Amazon EC2 or on-premises can optimize costs and engineering resources by using Amazon SageMaker AI with serverless …

Migrate MLflow tracking servers to Amazon SageMaker AI with serverless MLflow Read More »

Businesses face a growing challenge: customers need answers fast, but support teams are overwhelmed. Support documentation like product manuals and knowledge base articles typically require users to search through hundreds of pages, and support agents often run 20–30 customer queries per day to locate specific information. This post demonstrates how to solve this challenge by …

Build an AI-powered website assistant with Amazon Bedrock Read More »

Intelligent Document Processing (IDP) transforms how organizations handle unstructured document data, enabling automatic extraction of valuable information from invoices, contracts, and reports. Today, we explore how to programmatically create an IDP solution that uses Strands SDK, Amazon Bedrock AgentCore, Amazon Bedrock Knowledge Base, and Bedrock Data Automation (BDA). This solution is provided through a Jupyter notebook that enables users …

Programmatically creating an IDP solution with Amazon Bedrock Data Automation Read More »

Enterprise organizations increasingly rely on web-based applications for critical business processes, yet many workflows remain manually intensive, creating operational inefficiencies and compliance risks. Despite significant technology investments, knowledge workers routinely navigate between eight to twelve different web applications during standard workflows, constantly switching contexts and manually transferring information between systems. Data entry and validation tasks …

AI agent-driven browser automation for enterprise workflow management Read More »