AWS Messaging Blog

Category: Learning Levels

Building a Scalable Messaging API with AWS End User Messaging and SES

In this blog post, you’ll learn how to build a template manager and messaging API using API Gateway with JWT authentication for secure access, Amazon SQS for reliable message queuing, AWS Lambda for serverless processing, AWS End User Messaging for SMS, and Amazon Simple Email Service (SES) for email.

Build an AI-powered course recommender using Amazon Bedrock and AWS End User Messaging

Educational technology (EdTech) providers face the challenge of maintaining seamless, personalized communication and presenting the right recommendations to their diverse stakeholders. This post explores how combining Amazon Web Services (AWS) End User Messaging and WhatsApp Business API with the advanced AI capabilities of Amazon Bedrock can transform educational engagement.

Automate sender ID registration in AWS End User Messaging

This post explains how to programmatically register sender IDs, which can be used in many countries around the globe. The registration process makes it possible for businesses and organizations to send messages using an alphanumeric identifier instead of a phone number, making communications more professional and recognizable to recipients.

How to register for a US toll-free number with AWS End User Messaging

As businesses increasingly use SMS messaging to engage with customers at scale, having the right origination identity is crucial. Toll-free numbers (TFNs) are the quickest way to begin sending to the United States and offer a trusted, high-visibility option that can drive greater response and brand recognition. This post is for every company that wants to send to the US or internationally.

Best practices for building high-performance WhatsApp AI assistant using AWS

WhatsApp is one of the most widely used messaging platforms globally, making it an ideal channel for customer engagement. Whether you’re building a virtual assistant, a customer AI assistant, or an internal communication tool, developing a WhatsApp AI assistant presents unique design and operational challenges. In this post, we explore best practices for building a […]

Use AI agents and the Model Context Protocol with Amazon SES

We’ve released the SESv2 MCP Server sample on GitHub and invite current and prospective customers to experiment with it in non-production environments. This post provides example use cases demonstrating how the SESv2 MCP Server can be used with AI tools like the Amazon Q CLI to get information about an Amazon SES account, set up configurations, and send test emails – all without needing deep expertise in email or Amazon SES.

Building AI-powered customer experiences using a modern communications hub

Organizations face integration challenges while adding Generative AI (GenAI) -powered Agentic AI and hyper-personalization capabilities to engage with customers through dynamic and personal experiences. They require scalable and reusable architectures to integrate knowledge bases, business logic, and customer communications without a complete system overhaul, amid disparate engagement solutions they currently operate. A Modern Communications Hub, loosely coupled with core Generative AI services, will establish a composable foundation to build communication-channel-agnostic customer experiences on. Start experimenting with AI-powered customer experience innovations with a quick proof-of-concept that won’t interfere with your present customer engagement setup.