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We help business software to identify patterns and behavior from large volumes of operational data through machine learning.

Rather than explicitly programming custom software, our machine learning solutions help your information systems to think and predict outcomes on its own with sophisticated learning algorithms. 

Some of our popular solutions include recommendation engines for ecommerce sites, predictive sales channels, etc.

Our range of video, image and text analytics solutions can help your business to complete analysis works in a matter of hours which otherwise would have consumed weeks. 

Some of the solutions we have built include real-time video analytics of people in a storefront to generate insights about the product engagements, text sentiment analytics to understand and categorise the customer feedbacks and suggestions, image analytics solutions for product categorisation, quality analysis of products and similar product tagging and much more.

Predictive analytics helps your business by providing the best assessment of what will happen in the future. It uses the data, statistical algorithms, and machine learning to identify the likelihood of future outcomes based on the available historical data. 

The intelligent insights generated with predictive analytics can help to solve difficult problems and uncover new opportunities. 

Our expertise in predictive analytics solutions has helped several companies and startups in optimising marketing campaigns, improving operations, detecting fraud, reducing risks, increasing sales etc.

Build cognitive business technology frameworks that think like the human brain with deep learning. 

Using multi layered Artificial Neural Networks (ANN) we help your computer’s mimic human brain actions of perceiving complex and non-linear problems and responding to it as humans would. 

Our forte includes advanced speech and facial recognition systems, smart home automation systems, self-serving customer care chat bots and much more.

We’ve built model which can measure the distance between pedestrians in public places. Using a traffic light indicator system, the algorithm is able to anonymously identify and label people who maintain safe distances, while flagging certain instances in red where social distancing measures are violated. 

Using this information, it is possible to identify bottlenecks where social distancing cannot be maintained, and how citizens adapt as restrictions are imposed or lifted.

We’ve used Tensorflow and OpenCV to built this application. IMDB-2013 dataset and UTKFace dataset are used to train the custom model. This can be also used for eye color detection projects since it extracts eyes from a given image.

In this project we analyzed customer database, purchase history, renewal history, and CLSV to find the customers that are the most likely to purchase or upgrade. This reduced churn and shortened sales funnel and time to upgrade. 

Also, we looked at what made customers buy in the past to repeat the same process with new customers and make existing customers buy again. Through analyzing available data, we built predictive models that help shorten the time to convert and increase conversion rates.

We’ve have built data extraction tool that retrieves information in the key-value format and transforms documents into business-ready data better prepared for processing, analysis, and storage.