Tag: AWS Partner Success Stories

Learn how Accenture engineered a cloud-native SaaS learning platform that enables users to succeed in fast-paced environments. Take a look at why quick adoption is essential for an organization to acquire new knowledge, adapt mindsets, and develop new capabilities required to deliver changing business initiatives in a timely way. Accenture’s Future Talent Platform enables general or highly focused training to guide customers, partners, or employees to get the most out of new technologies or programs.

Learn how Rocketlane built its customer onboarding SaaS platform on AWS using the platform’s broad tools and services that helped the team innovate quickly, get support from programs such as AWS SaaS Factory, and go-to-market to reach customers through AWS Marketplace and AWS Activate for startups. In this Q&A with Deepak Balu, co-founder and CTO at Rocketlane, you’ll learn insights from Rocketlane’s journey that can help other organizations planning to adopt SaaS delivery model.

Datadog provides a unified view into the health and performance of your applications and infrastructure across both on-premises and AWS environments. Learn how to accelerate your migration by using Datadog’s observability capabilities to easily track every stage of migration to AWS. We’ll provide an overview of Datadog’s ability to optimize resources for migration, monitor availability of applications, and measure key business metrics around service-level objectives.

The AWS Cloud Development Kit (AWS CDK) allows developers to define their infrastructure as code using familiar programming languages. It simplifies the process of building, deploying, and managing infrastructure in AWS, making it a popular choice for organizations that want to improve their agility, reliability, and scalability. Learn how Attini helps you package your code, configuration, and deployment instructions into immutable artifacts. The Attini Framework will then automatically run your deployments for you.

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.

With more than 100,000 AWS Partners across the globe, how do you find the right partner for the right job? AWS Specializations help customers find a short list of trusted cloud partners with diverse expertise. Learn about the four programs that provide technical validation based on AWS services, workloads, use cases, industries, and managed services: Service Delivery, Service Ready, Competency, and Managed Service Provider (MSP).

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.

If your organization requires a faster time to market for Internet of Things (IoT) applications, AWS Partners have flexible, pre-built solutions to help reduce risk while building the foundational elements that are required to deploy an IoT solution at scale. Businesses interested in deploying an IoT solution should carefully consider which AWS Partner will best fit their organization’s needs, keeping in mind a few key elements, including capabilities, tenancy, security and compliance, migration, and pricing.

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.

Getting the same performance on open-source databases as you get on commercial-grade databases can be challenging. EPAM’s database assessment tool, migVisor, can play a key role in the overall migration methodology. Learn how using migVisor in combination with other AWS assessment solutions and services can help you gain a holistic view of your environment and make informed decisions to determine the feasibility of migrating your databases and correlated applications to AWS.