Category: Artificial Intelligence

Intelligent document processing (IDP) falls under the intelligent process automation of business tasks, and specifically involves extracting value from documents in an automated manner. Learn how customers can leverage Data Reply’s end-to-end IDP pipeline solution called DocExMachina, which is based on Amazon Textract and Amazon Comprehend. We’ll show how to make this pipeline document agnostic and customizable on AWS.

Sphere and Amazon Lookout for Vision are revolutionizing the way that high-value equipment and machines are assembled, maintained, and operated. By combining extended reality (XR) with AI, the integration gives manufacturing customers a cutting-edge tool to uncover process issues, identify missing components, detect damaged parts, and more. Explore use cases in which the enhanced training procedures and advanced analytics afforded by Sphere and Amazon Lookout for Vision can be applied to real-world scenarios.

Many public health agencies and laboratories still fax their test results and frequently change the format of those documents. Quantiphi’s Jim Keller speaks with AWS about the benefits of QDox, an intelligent document processing solution that leverages AI to recognize the document type, extract information, and deliver the output in the desired format. Quantiphi is an AWS Premier Tier Services Partner that’s a category-defining analytics, machine learning, and cloud modernization company.

Maintaining multiple machine learning models across different teams can be challenging. Having a centralized platform to monitor and manage them can significantly reduce operational overhead and improve efficiency. Learn how the models trained and deployed in Amazon SageMaker can be monitored by DataRobot in a highly scalable fashion. In this way, customers can monitor both DataRobot-originated models and SageMaker-originated models under a single pane of glass.

Gauging market demand for the apparel retail industry is challenging. The success of SKUs sold depends on customer preference (fitting, feel, regional acceptance) and latest trends, which can change frequently. Learn how Ganit has successfully deployed inventory management systems using intelligent demand forecasting at the core of its solutions. This system has helped many clients optimize their inventory, leading to efficient working capital deployment and improvement in topline and bottom-line numbers.

Rapid changes in business intelligence and analytics solutions means companies are continually over-investing in solutions that rapidly age. With DXC Technology’s Analytics and AI Platform (AAIP), you can develop and deploy new analytics applications in weeks. Learn about the features and benefits of AAIP, which helps you look further and deeper, gaining business insights from data you could not previously access or manage.

Managing existing brownfield buildings is a challenging task because teams usually lack accurate ground truth data. Object detection algorithms are a key technology to automate and scale the creation of a digital building twin, providing a solution to this challenge. For detecting objects in indoor environments with machine learning, learn how NavVis and AWS collaborated to build a digital building twin for a large industry customer.

Designing industry blueprints is driven by the need to address various challenges in package development for industry solutions. AWS Industry Blueprints for Data & AI (Preview) is an open-source initiative from that offers a collection of building components, including code modules and solution accelerators, to facilitate the configuration and deployment of tailored components for various industry verticals’ turn-data-to-insights needs.

Chatbot technology is rapidly revolutionizing customer experiences, providing businesses with a way to offer immediate and curated responses without allocating additional manpower and resources. For insurance companies, learn how using social media like WhatsApp in conjunction with Amazon Textract can make the claim process more streamlined and efficient, benefiting both customers as well as claim processing agencies. The objective is to simplify the claim process for any kind of expense.

When migrating on-premises MLOps to Amazon SageMaker Pipelines, customers often find it challenging to monitor metrics in training scripts and add inference scripts for custom machine learning models. Learn how Mission Cloud implemented an end-to-end SageMaker Pipeline to build the workflow of model development to production, accelerating their customer’s computer vision model production process. SageMaker Pipelines is a workflow orchestration tool for building ML pipelines with CI/CD capabilities.