Category: Artificial Intelligence
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.
Energy and process manufacturers are looking for mechanisms to predict asset breakdowns well before actual asset failure. Learn how Accenture Industrial Intelligence Suite addresses these challenges by using a strong data foundation, collecting and processing data from a variety of assets at scale. Accenture Industrial Intelligence Suite employs AI/ML models along with scalable AWS services to mitigate unplanned downtime, optimize asset performance, and improve asset reliability.
A digital twin is a virtual representation of a physical system that is dynamically updated with data to mimic the structure, state, and behavior of the physical system. Explore the results of MHP’s efforts working with AWS to build and deploy a Level 4 digital twin for an electric vehicle, as a means for monitoring and analyzing batteries of EVs utilizing live data, fleet knowledge, and AI. We’ll share a use case of battery health and performance management by learning driver behavior and battery characteristics from the fleet.
Traditional or click-based chatbots are relatively simple and provide a predetermined set of basic information or responses for users to choose from. Conversational AI bots, on the other hand, are more sophisticated and are best suited for enterprises with enormous data, ensure faster response time, and are available 24/7. Learn how to deploy bots within minutes using Infinity Botzer from LTIMindtree, and how this platform can facilitate comprehensive bot lifecycle management.
Feature engineering is a critical process in which data, produced by data engineers, are consumed and transformed by data scientists to train models and improve their performance. Learn how to accelerate data processing tasks and improve collaboration between data science and data engineering teams by applying MLOps best practices from Data Reply and leveraging tools from AWS. Data Reply is focused on helping clients deliver business value and differentiation through advanced analytics and AI/ML on AWS.