Products

Report, Plan, Predict, and Simulate Plant data in Real-Time to run all machines at optimum capacity and lowest costs. This solution works by capturing live data from the SAP S/4HANA system and visualizes it as graphs, charts, and tables using SAP Analytics Cloud Story and Analytical Application.

Customer churn refers to the loss of existing clients or customers. This solution identifies bank customers who are more likely to close their account and leave the bank. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

Customer churn refers to the loss of existing clients or customers. This solution identifies insurance customers who are more likely to close/not renew their policies with the insurance provider. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

This solution provides compositional analysis and predicts the number of incidents pertaining to each ticket group. The insights around incident distribution helps in proper capacity planning, resulting in efficient resource utilization.

Customer churn refers to the loss of existing clients or customers. This solution identifies mobile network subscribers who are more likely to change their operator. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

Customer churn refers to the loss of existing clients or customers. This solution identifies newspaper customers who are more likely to discontinue their current subscription. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

Customer churn refers to the loss of existing clients or customers. This solution identifies broadband customers who are more likely to discontinue their current broadband service provider. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data

Customer churn refers to the loss of existing clients or customers. This solution identifies E-commerce customers who are more likely to stop using the E-commerce app or the portal. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

netFactor Corporation is a leading provider of web visitor intelligence for B2B enterprises. netFactor’s flagship information service, VisitorTrack®, delivers real-time insights on the web...

5-Out is an innovative sales forecasting software specifically designed for restaurants, leveraging AI and next-gen machine learning technologies. With an impressive accuracy rate of up to 98%, 5-Out takes both internal and external data into consideration to accurately predict future demand. This software is your restaurant's oracle, telling you not just what you're going to sell, but also when you're likely to sell it. The result is optimized labor planning and efficient purchasing, helping t

The Depression Disease State Predictor is an advanced machine learning model designed to assess and predict the severity of depression in individuals. By analyzing multimodal physiological and digital activity data, this tool offers personalized predictions, aiding healthcare professionals in tailoring treatment plans more effectively. Key Features and Functionality: - Multimodal Data Analysis: Integrates various data sources, including physiological signals and digital activity, to provide a

The COPD Disease State Predictor is an advanced machine learning model designed to predict the risk of severe chronic obstructive pulmonary disease (COPD exacerbations. By analyzing patient data, it identifies individuals at high risk for hospitalizations related to acute COPD exacerbations, enabling timely interventions and personalized care plans. Key Features and Functionality: - Risk Prediction: Utilizes machine learning algorithms to assess the likelihood of severe COPD exacerbations, fac

The Colorectal Cancer Disease Predictor is an advanced tool designed to assess an individual's risk of developing colorectal cancer. By analyzing various factors such as age, family history, lifestyle habits, and medical history, this predictor provides a personalized risk assessment, enabling early detection and proactive management strategies. Key Features and Functionality: - Comprehensive Risk Evaluation: Utilizes a wide range of data points, including demographic information, personal and

The AMI Disease State Predictor is a machine learning model designed to predict the likelihood of Acute Myocardial Infarction (AMI, commonly known as a heart attack. By analyzing patient data, this tool aims to assist healthcare professionals in identifying individuals at risk, enabling timely intervention and personalized treatment plans. Key Features and Functionality: - Predictive Analytics: Utilizes advanced machine learning algorithms to assess patient data and predict the probability of

The Anemia Disease State Predictor is an advanced analytical tool designed to assist healthcare providers in identifying and managing anemia within patient populations. By leveraging comprehensive data analysis, this tool enables early detection of anemia, facilitating timely interventions and improved patient outcomes. Key Features and Functionality: - Comprehensive Data Integration: Aggregates and analyzes diverse patient data to identify patterns indicative of anemia. - Predictive Analytic

The Chronic Conditions Predictive Model is a sophisticated machine learning solution designed to forecast the likelihood of patients developing chronic diseases. By analyzing extensive healthcare datasets, this model identifies patterns and risk factors associated with chronic conditions, enabling healthcare providers to implement early interventions and personalized treatment plans. Key Features and Functionality: - Advanced Machine Learning Algorithms: Utilizes state-of-the-art algorithms to

The Lymphoma Disease State Predictor is an advanced machine learning model designed to assess and predict the progression of lymphoma by analyzing patient-specific data. This tool leverages deep learning algorithms to evaluate various clinical and histological parameters, providing healthcare professionals with a risk score that indicates the likelihood of disease progression. By integrating this predictor into clinical workflows, medical practitioners can make more informed decisions regarding

The Asthma Disease State Predictor is a cloud-based predictive modeling system designed to enhance the early detection and management of asthma. By leveraging advanced machine learning algorithms and real-time data analysis, this tool aims to predict asthma exacerbations, thereby improving patient outcomes and reducing emergency interventions. Key Features and Functionality: - Predictive Modeling: Utilizes machine learning techniques to analyze patient data and predict potential asthma exacerb

The Hypertension Disease State Predictor is an advanced machine learning model designed to assess the likelihood of hypertension in individuals by analyzing various medical attributes. Developed using the XGBoost algorithm and deployed on AWS SageMaker, this tool offers healthcare professionals a robust solution for early detection and management of high blood pressure. Key Features and Functionality: - End-to-End Machine Learning Pipeline: The model encompasses the entire process from data co