Data Analytics

How can we use data to make better decision? Data Analytics is the answer. What if the data that is important is not structured? It is just archives of emails and chats between employees and customers. If it is phone conversations archived as audio files? If it is reams of CCTV footage that is reviewed only after an event has occurred?  Analyzing such varied data to extract useful information and insights is what Data Analytics is all about.

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Machine Learning

What is Machine Learning? It is the art of training a software algorithm to learn from experience. Contrast this with traditional applications where the software follows the written logic. Those apps depend on the programmer. Machine learning apps depend on the data. As long as there is enough representative data in any format (text, videos, speech etc.,) these algorithms can be trained to do almost anything.

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Not just Cloud AI, but Edge AI

Lots have been written about AI and the Cloud. But the latest buzz is all about doing Machine Learning on the edge i.e on a small, cheap device with limited computing power. Like our cellphones or embedded Single Board Computers like Rasberry Pi etc., The Machine Learning models are becoming smaller and these edge devices are getting faster, that we can finally do useful machine learning apps on these devices. We spend lot of time building these small Machine Learning models that are robust and yet can run on your phone.

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Cognitive Process Automation

Front-end automation by recording a user’s mouse and key strokes has truly come to the main stream. In industry speak, this is called Robotic Process Automation (RPA). The most important advantage of RPA is its quick turn around and ability to incorporate automation in an iterative manner. This results in minimum disruption to existing processes and almost no expensive back-end changes.

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