Category: Learning Levels

Industry 4.0 increases product complexity and customer expectations, challenging industrial companies. Tech Mahindra’s Engineering on Cloud – PLM solution leverages AWS to help manufacturers centralize product data management and accelerate innovation. This cloud-native solution optimizes costs and provides enhanced security, scalability, and availability with faster time-to-market and streamlined collaboration.

Customers implementing sophisticated solutions based on AWS technologies often seek out qualified partners who bring their industry expertise to the table and help accelerate a return on investment (ROI) that achieves business outcomes faster. Partner-Led Support offers AWS Partners the opportunity to expand their sources of recurring revenue by complementing and supplementing AWS capabilities in delivering technical support to customers.

Intelligent document processing (IDP) automates data extraction from diverse document formats, accelerating information retrieval. Manually labeling is expensive and difficult, and Cognizant’s IDP solution on AWS automates document labeling at scale to overcome this challenge. Its customized user interface in Amazon SageMaker Ground Truth lets subject matter experts efficiently label documents.

Discover how a collaboration with AWS SaaS Factory revolutionized nClouds’ approach to SaaS and empowered its team to amplify its capabilities. Leveraging SaaS Factory’s technical knowledge equipped nClouds with the assurance and actionable insights needed to conquer the intricacies of the SaaS cloud landscape. For customers like OperationsRx, aligning with a SaaS Competency Partner like nClouds meant tapping into a reservoir of expertise, strengthened by years of experience from industry-leading experts.

As online commerce grows, so do opportunities for fraud. Businesses lose billions annually to bots and attacks like scraping and payment fraud, making effective and scalable protection essential. DataDome provides accurate, real-time detection and mitigation without compromising user experience. By deploying globally on AWS and optimizing performance, DataDome achieves sub-millisecond response times to inspect every request while minimizing false positives.

Skuid by Nintex is a low-code platform for rapidly building enterprise web apps. This post demonstrates using Skuid to connect to Amazon S3, listing bucket contents in a table, and enabling upload, download, and delete actions. With just a few configuration steps and zero coding, Skuid integrates data from services like S3 into polished, branded experiences, and streamlines building cloud-native apps without compromising power or flexibility.

As networks become more complex, telcos need an integrated platform to manage monitoring, diagnostics, and automation. Prodapt worked with AWS to build a cloud-native, open-source network assurance platform called NeSA. It provides a single pane of glass for end-to-end visibility, faster troubleshooting, and closed-loop automation. This post details Prodapt’s experience implementing NeSA for a Tier 1 telco, reducing incident resolution time and costs.

Large language models like Amazon Bedrock can generate MongoDB queries from natural language questions, transforming how users access NoSQL databases. By leveraging AI and language models, this solution allows business users to query MongoDB data through conversational English instead of code. It connects to MongoDB with PyMongo, generates queries with LangChain and Bedrock, retrieves and formats results into natural language answers.

As organizations modernize mainframe applications, integrating mainframe batch workloads into cloud environments is a key challenge. Stonebranch’s scheduler integrates with AWS Mainframe Modernization service to enable centralized, automated scheduling and monitoring of mainframe batch jobs on the cloud. This improves efficiency, optimizes costs, and accelerates mainframe modernization by enabling seamless workload orchestration across legacy and modern platforms.

MLOps applies DevOps principles to machine learning, enabling organizations to efficiently develop, deploy, and manage models at scale. Eviden’s 10-step MLOps assessment examines existing models, establishes governance, creates self-service access, scales data analysis, registers models, enables feature re-use, provides data access, tests models at scale, deploys models, and enables API access. This end-to-end approach streamlines model creation and deployment while ensuring governance and consistency.