AWS AI Services: The Most Useful AWS AI / ML Tools For Building Content-Centric Digital Experiences

With the introduction of generative AI, Amazon Web Services (AWS) has expanded its list of tools enabling organizations to leverage them to create personalized and engaging content, including everything from personalized enterprise websites and customer portals to corporate intranets, eCommerce experiences, and OTT video applications. 

Let’s look at the AI and ML tools AWS offers and how they can be used alongside an AWS CMS such as CrafterCMS.

Why AWS For Content-Centric Digital Experiences?

AWS remains the dominant force in cloud computing services and infrastructure. The market leader held 32% of the global market share as of Q2 2023 and continues to provide an assortment of services that enterprises can leverage to engage in a host of activities, including creating content-rich experiences. 

Delivering the varied content experiences that power enterprises today requires scalability, reliability, security, and the ability to integrate with different systems. AWS offers these characteristics in spades and an infrastructure spanning over 30 different regions. This and an extensive list of services make AWS an ideal solution for supporting modern digital experiences. 

Regarding generative AI and machine learning applications, AWS has been at the forefront of these technologies for quite some time. Now the cloud service provider has doubled down to provide even more services that enable businesses to take advantage of opportunities and deliver more value for enterprises looking to build AI-enabled content-driven digital experiences.

AWS AI Services For Content-Centric Applications

• Amazon Augmented AI (A2I): Enables organizations to implement human reviews and audits of ML predictions based on specific requirements. This helps guarantee precision and can be used to extract critical information from documents, such as those in the healthcare industry. 
  
• Amazon CodeGuru Security: A static application security testing (SAST) tool that uses machine learning capabilities to detect, track and fix vulnerabilities in code security throughout the development cycle.
  
• Amazon Comprehend: A natural language processing (NLP) service that can uncover and understand insights from text within documentation using machine learning. This can be useful for indexing key phrases and sentiments in content, not just keywords.
  
• Amazon Comprehend Medical: For health care industry sites and apps, Comprehend Medical extracts information from unstructured medical content to automate processing, lower costs, accelerate business activities such as insurance claim processing, improve overall health outcomes, and more.
  
• Amazon DevOps Guru: A tool that leverages machine learning to detect issues before they impact the customer experience. DevOps Guru helps scale and maintain application availability and identify early warning signs before they become larger problems. 
  
• Amazon Fraud Detector: This tool leverages both your own data and Amazon’s 20+ years of online experience to detect fraudulent online activities. Use this services to detect new account fraud, suspicious online payments, loyalty program abuse, account takeovers, and more. 
  
• Amazon Kendra: An enterprise text extraction tool that can be integrated into document-centric digital experiences such as customer portals, automatically extracts text, handwriting, and data from scanned documents. This AWS AI service provides sophisticated optical character recognition (OCR) to identify, understand, and extract data from forms and tables too. 
  
• Amazon Lex: A tool for building chatbots using conversational AI, which can enhance self-service functionality for customers visiting corporate websites, portals, e-commerce sites among others.
  
• Amazon Lookout for Metrics: Identify false positives and other anomalies in metrics using machine learning. This tool is useful for measuring business or content performance and can help organizations to optimize their spending on ads and other paid content experiences. 
  
• Amazon Personalize: Machine learning-powered personalization to enhance the customer experience. With Personalize, organizations can achieve more granular targeting of customers with content and provide better recommendations.
  
• Amazon Polly: Using deep learning techniques, Polly can synthesize natural-sounding speech, converting textual content and making it easy to add speech to websites, portals, mobile apps, and more.
  
• Amazon Rekognition: Computer vision capabilities that can extract insights from images, videos, automating image recognition. This helps organizations to detect inappropriate content and streamline media analysis.
  
• Amazon Textract: With Textract, companies can use machine learning to extract text, handwriting, and other data from scanned documents such as PDFs.
  
• Amazon Transcribe: This AWS AI service provides automatic speech to text conversion. Amazon Transcribe Subtitling can capture the audio from meetings and conversations, and automatically subtitle your video-on-demand and live-streaming broadcast content to increase accessibility and enhance customer experience.
  
• Amazon Translate: Use AWS Translate to expand the reach of your sites and apps to multi-national and global audiences, with automatic language translation that can provide accurate, quick, and customizable translated output.

AWS ML Services For Content-Centric Applications

AWS offers ML services such as Amazon Bedrock and Amazon Sagemaker that enable developers to build, deploy and scale AI and machine learning applications to fit a variety of digital experience use cases. 

• Amazon Bedrock: This AWS ML service makes foundation models (FMs) from Amazon and leading AI startups available through an API, allowing enterprises to choose FMs to find the model that's best suited for any particular use case. With the Amazon Bedrock serverless experience, you can quickly get started, easily experiment with FMs, privately customize FMs with your own content, and seamlessly integrate and deploy them into your sites and apps. Example applications include generative AI (text and images) for website content, social media posts, and blogs, conversational interfaces such as virtual assistants and chatbots, personalized recommendations, and text summarization.
  
• Amazon Sagemaker: This AWS ML service provides fully managed infrastructure, tools, and workflows to build, train, and deploy machine learning (ML) models for a wide range of use cases. This comprehensive service enables enterprises to quickly leverage AWS’ over 20 years of experience developing real-world ML applications, including product recommendations, personalized experiences, intelligent shopping, and voice-assisted devices.

Maximizing the Capabilities of AWS AI/ML with an AWS CMS

CrafterCMS is a headless CMS that fully leverages the power of AWS infrastructure to deliver content-rich, digital experiences at scale. With CrafterCMS, global enterprises can leverage several out-of-the-box integrations with AWS in the CrafterCMS Marketplace. For developers, CrafterCMS provides comprehensive APIs (REST, GraphQL, among others) and server-side scripting (via Groovy and/or Javascript) to easily integrate new AI/ML services as well.

Watch: Building AI Chatbots with a Headless CMS on AWS 

CrafterCMS’s private SaaS offering, Crafter Cloud, natively runs on AWS infrastructure as well, making integrations and deployment straightforward. AWS EC2 forms the foundation of the Crafter Cloud’s compute infrastructure. On top of that, Elastic Kubernetes Service (EKS) provides the Kubernetes and Docker layer, which provides a multi-regional serverless and stateless operating environment. 

Also natively integrated into Crafter Cloud, AWS OpenSearch provides the embedded search engine for content search/retrieval within the content authoring experience, and serves as the basis for the search API for developers. Crafter Cloud also leverages EBS and S3 for storage, Cloudfront for CDN, and AWS WAF for additional security.

To learn more, check out our recorded webinar: AI-Based Media Asset Management with AWS Rekognition and CrafterCMS