Products

PVSOL is a dynamic simulation software designed for the planning, design, and optimization of photovoltaic (PV) systems. It caters to a wide range of projects, from small residential installations to large commercial and utility-scale systems. The software enables users to model various PV configurations, including grid-connected and off-grid systems, with or without battery storage and electric vehicle integration. By providing detailed performance analyses and financial assessments, PVSOL assi

Ultria Orbit personifies Ultria’s Artificial Intelligence capabilities, helping you streamline workflows across your contract lifecycle, through timely suggestions, diagnosis and predictions, for error-free and dynamic contracts.

Bloomberg Law is a comprehensive, subscription-based legal research and workflow platform that integrates primary and secondary legal content, proprietary news, analytics, and practical guidance into a unified system. Launched in 2009 by Bloomberg L.P., it combines real-time legal intelligence with Bloomberg's extensive financial and business data resources, serving attorneys, law students, and other legal professionals. Key Features and Functionality: - AI-Powered Tools: Utilizes artificial i

TekVision's Automated Web Chat Testing solution is designed to optimize automated chat systems, ensuring seamless digital customer interactions without the need for live agent support. By thoroughly emulating live customer interactions, this solution identifies and addresses shortcomings in chatbot programming, enhancing both customer satisfaction and organizational efficiency. Key Features and Functionality: - Comprehensive Testing: Accurately emulates live customer interactions to iden

Shipium's Machine Learning (ML platform revolutionizes supply chain operations by providing real-time predictions of shipping speed, cost, and accuracy. By integrating advanced ML models, Shipium enables businesses to optimize fulfillment processes, enhance delivery precision, and reduce operational expenses. This technology empowers operators to make informed decisions, ensuring efficient and reliable shipping performance. Key Features and Functionality: - Dynamic Time-in-Transit Modeling: Pr

Effective scheduling for hospital admission is a major challenge as there is uncertainty in patient’s length of stay and large errors in estimations can lead to capacity pressures. To tackle this, Virtusa-GCTS has developed a Deep Learning based solution which will accurately predict how long a newly admitted patient will stay in the hospital. The model uses cutting edge regression algorithms. This model not only helps Hospitals to plan and deploy their resources effectively but also helps insur

The Aviator Predictor is a crash predictor tool that analyzes SHA-256 and SHA-512 hash data to visualize rounds and explore patterns. It helps users study hash-based systems and test prediction models in demo environments.

Kumo.AI is a SaaS platform that empowers organizations to build and deploy advanced predictive AI models directly from their relational data. By leveraging state-of-the-art Graph Neural Networks , Kumo.AI eliminates the need for manual feature engineering, enabling users to generate accurate predictions efficiently. The platform is designed to be accessible to both technical and non-technical users, facilitating the development of AI models without extensive machine learning expertise. Key Fea

Fleksy is a world-class virtual keyboard for iOS and Android. Serving millions of users around the globe every second of every day, Fleksy holds the Guinness Book of World Records as the fastest keyboard in the world and is the best option when privacy matters. Unlike most other keyboards, Fleksy’s AI algorithm is crazy small at just 2-4MB we are able to localize it on your device, ensuring that your typing data is never sent to the cloud or stored anywhere. The Fleksy SDK is our Software Deve

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 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 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 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 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 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.

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 Alzheimer's Disease State Predictor is a sophisticated machine learning model designed to assess and predict the progression of Alzheimer's disease in patients. By analyzing a comprehensive range of patient data, including demographics, clinical history, and diagnostic results, this tool provides healthcare professionals with valuable insights into disease trajectories, facilitating early intervention and personalized treatment planning. Key Features and Functionality: - Comprehensive Data

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