Machine Learning Data Classification
It is difficult to imagine a modern banking system, like other financial-related services, without IT technologies that not only allow processing large amounts of data but also significantly reduce the possibility of human error and data leaks.
Primarily for working with financial services (for example, banks and insurance companies), the Softengi team has developed a Data Classification Solution that allows financial institutions to mark and classify data, as well as to detect anomalies. It may not only minimize human errors but even provide superhuman performance in some stack of tasks.
This application uses the latest advanced approaches of Artificial Intelligence and Machine Learning to provide users with instant data analysis results. Also, thanks to Microsoft Azure, users’ data is safe and accessible 24/7 without the risk of its destruction and theft.
Data classification in data mining is one of the fundamental tasks in AI, and with contemporary ML algorithms, it lets users classify your data.
Our team of specialists can provide your company with the introduction of modern technologies in less than six months. Plus, your employees will work with a simple and intuitive interface based on the latest UX and UI design trends.
Creating an application includes prototyping, development, and training of ML algorithms and setting up work processes.
Several indisputable benefits of Machine Learning Data Classification
Thanks to the use of modern technology and MS Azure, the user can quickly work with large amounts of data.
It is easy to detect anomalies in the classification using neural networks trained to look for errors.
Machine learning will eliminate errors from work caused by the inattention of employees.
Some additional perks of using Machine Learning Data Classification:
- Data security: the use of Azure eliminates the possibility of information leaks and keeps data safe.
- Quick processing: modern technologies on which the Solution is based allow you to quickly process and classify large amounts of data.
- Error reduction: thanks to automatic processing and classification of data using machine learning, the likelihood of human error is eliminated.