Category: Artificial Intelligence

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.

The AWS Machine Learning Visionaries Partners Report is a quarterly series that tracks, selects, collates, and distributes horizontal technology capabilities enabled by machine learning in areas that AWS expects to be transformative in 1-3 years. The series’ purpose is to share our insights with AWS Partners and to collect their interest, expertise, and insights in co-building along these prioritized themes. The reports include updates on series topics as we see changes in those areas, and new topics will also be added.

Infusing machine learning into core business processes such as credit scoring creates a competitive edge for banks and financial services institutions. It does not require a data science team, expertise, or platform rollout. Explore an ML-based credit-decisioning model built by ElectrifAi in collaboration with AWS whose model rapidly determines the creditworthiness of a SME, and data-driven, actionable insights reduce the overall processing cost and are consistent and free from any potential human biases.

Many organizations record calls which are potential gold mines of rich insights about customer satisfaction, customer churn, competitive intelligence, service issues, agent performance, and campaign effectiveness. However, the sheer volume of phone calls exceeds a contact center’s ability to review and analyze them in order to glean those valuable insights. Learn how SourceFuse used custom microservices development to design a call center solution for a healthcare customer.

With the rise of voice assistants like Amazon Alexa, customer expectations for handling inquiries and transactions have shifted from the outdated phone keypad, also known as dual tone multi-frequency (DTMF), to modern conversational AI that enables machines to communicate with human beings. In this post, we demonstrate how Presidio implemented conversational AI to check the wait time and reserve a table at a restaurant using Amazon Chime SDK, Amazon Lex, and Amazon Polly.

Featurization is one of the most difficult problems in machine learning. Learn how graph features engineered in Neo4j can be used in a supervised learning model trained with Amazon SageMaker. These novel graph features can improve model performance beyond what’s possible with more traditional approaches. Together, these components offer a graph platform that can be used to understand graph data and operationalize graph use cases.