Category: Artificial Intelligence

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.

We are excited to announce the new AWS Conversational AI Competency launching in Q1 2023, which helps enterprises implement high-quality, highly effective chatbot, virtual assistant, and IVR solutions through the expertise of AWS Partners. AWS Conversational AI Competency Partners provide domain expertise, tools, and services to aid in selecting use cases, defining Natural Language Understanding (NLU) Intents and training phrases, designing effective conversational flows, and more.

We’re excited to announce the launch of the Amazon SageMaker Ready specialization for AWS Partners with Amazon SageMaker software offerings. Through this specialization, customers can identify software solutions that integrate with Amazon SageMaker—allowing them to seamlessly solve use cases and innovate with machine learning. Software offerings include data platforms, data pre-processing and feature stores, ML frameworks, MLOps tools, and business decisioning and applications.

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.

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.

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.

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.

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.

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.

Federated learning (FL) addresses the need of preserving privacy while having access to large datasets for machine learning model training. The NVIDIA FLARE (which stands for Federated Learning Application Runtime Environment) platform provides an open-source Python SDK for collaborative computation and offers privacy-preserving FL workflows at scale. NVIDIA is an AWS Competency Partner that has pioneered accelerated computing to tackle challenges in AI and computer graphics.