Sensis

Sensis, the flagship application of Ranfor Consultin, harnesses the power of machine learning and data mining on mobile devices. This is a Free mobile application, which analyzes sentiments on mobile devices.

Sensis combines the power of machine learning and data mining. Powered by a unique and scalable algorithm, this highly useful app brings sentiment analysis on mobiles & tablets.

In the past, these algorithms were thought of running on large machines with incredible power. Businesses needs answer quickly and close, and Sensis helps in these areas. Sensis performs sentiment analysis on huge volumes of data on small devices and tablets.

As in machine learning, the application is designed to learn itself. So after every run, the program is armed with the new found intelligence and uses this subsequently, so the results become more accurate overtime.

Some remarkable features of Sensis:
. Processes big files - Sensis can process big files upto 20 MB. The free version has a limitation of file size only upto 5 MB
. Advanced Reporting is available on demand (but not in Free version). This report helps understand the performance of a particular actor/ attribute/ variable (over a period)
. Self learning algorithm within Sensis uses some advance concepts of Machine learning. The sentiment analysis continuously learns and boosts itself as more and more data is analyzed.

This app can be applicable in a variety of contexts, such as:
. analyzing customer feedback for a wide range of industries (BPO, Call Centres, KPO, Tourism etc.)
. during product evaluation the app can signal about what are the products that have generated favorable feedback
. analyzing data related to tourism/ travel (e.g.out of a number of places, which is most sought after, or based on a number of facilities, which one is good and which one is bad)
. can be used in sentiment analysis for healthcare industry on the feedback/satisfaction survey of patients/customers
. during recruitment process while screening candidates’ responses
. analyzing responses of any survey
. for manufacturing processes
. customer feedback can be analyzed to understand the effectiveness of processing units
. while analyzing Medical trials the responses can be analyzed on various factors such as geography, ethnic groups etc.