Today’s world is witnessing some outstanding AI enabled applications that yields huge opportunities for industries to resolve their real time problems and generate value for their businesses. Amper’s collaborative ecosystem with AI uses training and validation data to help a model gain insight to enable it to predict outcomes from similar data patterns. The model uses the learning acquired to forecast future behaviour, patterns and trends accurately without being explicitly programmed for this task.
Amper’s high scalable algorithms ensure that the system is efficient even if the complexity of the input data increases.
The ML model can be integrated with process, event or data models effortlessly. The Machine Learning model can be integrated with the Data Flow model to enhance data preparation capabilities.
The Event Stream model along with ML model can be used for predictive analysis of live streams of data.
Amper’s AI powered platform automatically determines the best algorithm for a model based on the type of input parameter.
Amper’s visual drag-drop development environment enables quick design of ML model to generate predictions.
Visual representation of the machine learning algorithm and its outcomes, facilitates the user to choose the best ML model.
The prediction intelligence of the model is improved through continuous learning and re-training.
When a ML model is re-trained, the Confusion Matrix in Amper forecasts the accuracy of the prediction of the trained model.
Third Party integrations can be done with ease in Amper with the help of API’s.
A dialysis service provider spread across the country, selected Amper's AI powered application platform as a Service(aPaaS) to build an intelligent, predictive and data driven healthcare solution that provides proactive medical attention to patients registered with their centres to prevent lapses that might result in emergencies.
A multi-utility company wanted to enhance the management of their devices spread across the globe. Amper’s AI powered Analytics platform provided the required technology to build a predictive maintenance solution for tracking and monitoring assets remotely to speculate possible device failures, detect device usage and location.
Poor insights into credit risks hamper financial institutions through conservative lending decisions, high credit losses, costs of capital and slow market turnaround time. A well-known financial institution that specializes in corporate loans used Amper's robust, secure and flexible analytics platform to gain insights into market risks through predictive analytics.
When customer responses and tweets became more frequent and demanding, a multi-national consumer brand had to find an efficient way to handle negative tweets in-time. Amper provided a Natural Language Processing Solution seamlessly integrated with several external systems to analyse the nature of tweets and respond to the them promptly.