AWS Architecture Blog

Category: Artificial Intelligence

Architecture diagram

Enhance Your Contact Center Solution with Automated Voice Authentication and Visual IVR

Recently, the Accenture AWS Business Group (AABG) assisted a customer in developing a secure and personalized Interactive Voice Response (IVR) contact center experience that receives and processes payments and responds to customer inquiries. Our solution uses Amazon Connect at its core to help customers efficiently engage with customer service agents. To ensure transactions are completed […]

Figure 2. Credit application – technical solution using Amazon SageMaker and Experian CaaS ML models

How Experian uses Amazon SageMaker to Deliver Affordability Verification 

Financial Service (FS) providers must identify patterns and signals in a customer’s financial behavior to provide deeper, up-to-the-minute, insight into their affordability and credit risk. FS providers use these insights to improve decision making and customer management capabilities. Machine learning (ML) models and algorithms play a significant role in automating, categorising, and deriving insights from […]

Figure 3. FL prototype deployed on Amazon ECS Fargate containers and AWS IoT Greengrass cores.

Applying Federated Learning for ML at the Edge

Federated Learning (FL) is an emerging approach to machine learning (ML) where model training data is not stored in a central location. During ML training, we typically need to access the entire training dataset on a single machine. For purposes of performance scaling, we divide the training data between multiple CPUs, multiple GPUs, or a […]

Figure 2. Extending the solution

Scale Up Language Detection with Amazon Comprehend and S3 Batch Operations

Organizations have been collecting text data for years. Text data can help you intelligently address a range of challenges, from customer experience to analytics. These mixed language, unstructured datasets can contain a wealth of information within business documents, emails, and webpages. If you’re able to process and interpret it, this information can provide insight that […]

Figure 1. Architecture for batch inference at scale with Amazon SageMaker

Batch Inference at Scale with Amazon SageMaker

Running machine learning (ML) inference on large datasets is a challenge faced by many companies. There are several approaches and architecture patterns to help you tackle this problem. But no single solution may deliver the desired results for efficiency and cost effectiveness. In this blog post, we will outline a few factors that can help […]

Figure 1. Well-Architected Machine Learning Lifecycle

Introducing the new AWS Well-Architected Machine Learning Lens

The AWS Well-Architected Framework provides you with a formal approach to compare your workloads against best practices. It also includes guidance on how to make improvements. Machine learning (ML) algorithms discover and learn patterns in data, and construct mathematical models to predict future data. These solutions can revolutionize lives through better diagnoses of diseases, environmental […]

Field Notes: Build a Cross-Validation Machine Learning Model Pipeline at Scale with Amazon SageMaker

When building a machine learning algorithm, such as a regression or classification algorithm, a common goal is to produce a generalized model. This is so that it performs well on new data that the model has not seen before. Overfitting and underfitting are two fundamental causes of poor performance for machine learning models. A model […]

Top 5

Top 5: Featured Architecture Content for September

The AWS Architecture Center provides new and notable reference architecture diagrams, vetted architecture solutions, AWS Well-Architected best practices, whitepapers, and more. This blog post features some of our best picks from the new and newly updated content we released in the past month. 1. AWS Best Practices for DDoS Resiliency Prioritizing the availability and responsiveness […]

Figure 8. Architecture diagram of entire data collection and classification process

Serverless Architecture for a Structured Data Mining Solution

Many businesses have an essential need for structured data stored in their own database for business operations and offerings. For example, a company that produces electronics may want to store a structured dataset of parts. This requires the following properties: color, weight, connector type, and more. This data may already be available from external sources. […]

Field Notes: How to Prepare Large Text Files for Processing with Amazon Translate and Amazon Comprehend

Biopharmaceutical manufacturing is a highly regulated industry where deviation documents are used to optimize manufacturing processes. Deviation documents in biopharmaceutical manufacturing processes are geographically diverse, spanning multiple countries and languages. The document corpus is complex, with additional requirements for complete encryption. Therefore, to reduce downtime and increase process efficiency, it is critical to automate the […]