This Guidance demonstrates how Nonprofits can drive higher engagement with donors/members by building an intelligent omni-channel contact center leveraging AWS Artificial Intelligence/Machine Learning and Omnichannels contact center services.

Architecture Diagram

Download the architecture diagram PDF 

Well-Architected Pillars

The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

Sample Code

Start building with this sample code. Learn how to automate business processes which presently rely on manual input and intervention across various file types and formats.

AWS Machine Learning Blog
Content moderation design patterns with AWS managed AI services
User-generated content and its value to gaming, social media, ecommerce, and financial and health services organizations will continue to grow. Still, startups and large organizations need to create efficient moderation processes to protect users, information, and the business, while lowering operational costs.
This post demonstrates how AI, ML, and NLP technologies can efficiently help you moderate content at scale.
Read the full blog post 
AWS Machine Learning Blog
Utilize AWS AI services to automate content moderation and compliance
Content moderation is fundamental to protecting online communities, their members, and members’ personal information. There are also strong business reasons to reconsider how your organization moderates content.

In this post, we discuss how you can automate content moderation and compliance with artificial intelligence (AI) and machine learning (ML) to protect online communities, their users, and brands.
Read the full blog post 
AWS Machine Learning E-book
Protect your users, brand, and budget with AI-powered content moderation
As the volume, complexity, and speed of user generated content (UGC) increase, organizations of all sizes must commit significant technical and human resources to ensure customers are not exposed to offensive material. 
In this e-book, we discuss how AWS has AI solutions and services that can be self-managed or customized to help you create safe online communications and protect your customers and brand, all while reducing moderation costs.
Read the full e-book 


The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.