ARTIFICIAL INTELLIGENDE (AI) IN THE PAST 2 DECADES IS WIDELY ADOPTED BY MAJOR TECHNOLOGICAL
Companies such as Google, Facebook, IBM and Apple for solving a plethora of problems. This process of adoption is mainly has been credited to the flourishment of Machine Learning (ML) and a subset of its methods called “Deep Neural Networks” in the recent years. Using ML these companies are enabled to solve their unresolved problems in a limited boundary in case of computational resources and time.
We in Miras (with the mindset of being the pioneers of applying AI algorithms to real world problems in the world) have also started to apply many of the most recent methods for solving a set of various problems such as
- Associations Rules Mining and Affinity Analysis,
- Time Series Analysis,
- Optical Character Recognition (OCR),
- Speech Recognition,
- Text Analysis,
- Sentiment Analysis,
- Convex Optimization,
These methods have been used to solve customer problems in many area of the market. Using our expertise and the cutting-edge tools mainly based on R and Python programming languages we were able to shed light on many of your problems and solve them.
In Public Relations (PR), it is the value that can be created to improve performance, and better understand competitors, consumers, employees, media, and other publics. Organizations must learn and recognize that data alone do not answer “why” or explain inferred insights.
There is big insight in Power industry using ML methodology to make the power grid to operate a lot more intelligently. To take a step in this path we have developed predictive maintenance for power plant to forecast the maintenance scheduling and make their operation much more efficient.
Our analytical back end give airlines a critical look at passengers to enable better and more personalized experiences for each passenger, which in turn drives brand loyalty, increases customer satisfaction, enables stronger auxiliary revenue stream and finally supports scheduling/rebooking of passengers when delays occur.
In marketing our analytical back end based on our technologies is providing insights into which content is the most effective at each stage of a sales cycle, how Investments in Customer Relationship Management (CRM) systems can be improved, in addition to strategies for increasing conversion rates, prospect engagement, conversion rates, revenue and customer lifetime value.