AWS Partner Network (APN) Blog

Tag: Machine Learning

Building a Predictive Maintenance Solution Using AWS AutoML and No-Code Tools

Learn how equipment operators can build a predictive maintenance solution using AutoML and no-code tools powered by AWS. This type of solution delivers significant gains to large-scale industrial systems and mission-critical applications where the costs associated with machine failure or unplanned downtime can be high. The design of this solution is based on the experience of Grid Dynamics with manufacturing clients.

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Making Accounts Payable Simpler and Faster with Amazon Textract-Based X·CELERATE Invoice

Learn how AWS and Xoriant are working together to offer a service that assists any firm with their invoicing needs through X·CELERATE Invoice and Amazon Textract. This post covers the key steps of this system and how the collaboration between AWS and Xoriant is building better invoicing solutions for companies dealing with hundreds, if not thousands, of invoices each month. Learn why automated invoice processing (AIP) is important and how AWS and Xoriant are fueling innovation in AIP.

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Operational Analytics with MongoDB Atlas and Amazon Redshift

Enterprises are building data analysis capabilities to extract information captured in data, develop an understanding of their business, and channel efforts towards customer centricity. This post explains the need for operational analytics and how it can be achieved with MongoDB Atlas and Amazon Redshift. MongoDB is an AWS Data and Analytics Competency Partner and developer data platform company empowering innovators to unleash the power of software and data.

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Teradata Vantage Real-Time API Integration with Amazon SageMaker Endpoints

Teradata has expanded its collaboration with AWS by adding integration capabilities for Teradata Vantage, the data platform for enterprise analytics and AWS cloud services. Vantage, with its NOS read/write connector to Amazon S3 data, already provides data integration with S3 data and Vantage enterprise data. Now, Teradata introduces an API integration with Amazon SageMaker and Amazon Forecast. This enables business users to drive outcomes with real-time analytics.

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How Blue People Detected Application Anomalies Using Insights from Amazon DevOps Guru 

Amazon DevOps Guru is a machine learning-powered service that detects abnormal application behavior and provides insights about the anomalous behavior. These insights are supported with metrics and events related to the anomaly and recommendations to help address and mitigate the anomalous behavior. Learn how Blue People used insights to identify the root cause for a non-responsive application that was otherwise hard to detect.

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Engage360 is an Amazon Kendra-Powered App to Optimize Search and Recommendation Experience in Salesforce CRM

Engage360, built by Persistent Systems and powered by Amazon Kendra, is a security-certified app on Salesforce AppExchange that lets you provide machine learning-powered search and recommendations right inside Salesforce Sales Cloud, Salesforce Service Cloud, and Salesforce Financial Services Cloud. It transforms how Salesforce users securely discover, access, and deliver relevant knowledge distributed across disparate enterprise information silos and content formats.

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How to Accelerate SAP Insights with Qlik, Snowflake, and AWS

Sales order fulfillment and billing can impact customer satisfaction, and receivables and payments affect working capital and cash liquidity. As a result, the order-to-cash process is the lifeblood of the business and is critical to optimize. Qlik Cloud Data Integration accelerators integrate with Snowflake to automate the ingestion, transformation, and analytics to solve some of the most common SAP business problems, enabling users to derive business insights that can drive decision-making.

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Powering Business Process Automation with Machine Learning Using Pega and Amazon SageMaker

Through the Pega Platform and Amazon SageMaker, you can easily streamline the development and operationalization of machine learning models to improve process automation. This allows customers to combine the strengths of cloud, data, and machine learning with AI-powered decisioning and smart workflow capabilities. It also enables customers to operationalize and monetize data and insight, drive process efficiency and effectiveness, and improve customer experience and value.

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How Ganit Helps Customers Optimize Their Inventory by Leveraging Amazon Forecast

Predicting demand for medical products can be a formidable challenge, since many items have no underlying seasonality patterns nor a consistent shelf life. Learn how Ganit worked with a client to achieve reductions in inventory by designing a robust solution with Amazon Forecast. This post details the approach used to define the objectives and discover the data treatments, and cover employing the flexible architecture provided by Forecast to turn the client’s data into a strength.

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What Do Consumers Really Think of Automated Customer Service?

Conversational AI solutions, like chatbots and interactive voice response systems (IVR), are a key component of enterprises’ customer service strategy. AWS recently ran a survey, through ESG, on consumers’ opinions of automated customer service solutions like chatbots and IVRs. Conversational AI solutions have come a long way from basic FAQ experiences, and while we see strong positive signals of consumer interest in automated solutions, there are still areas for improvement.