One of the biggest problems recruiters face to this day is the lack of a system to find deserving candidates for a specific job. We built a Machine Learning model that matches the right candidates to the right job using not just their resumes, but social data and a number of other parameters such as GitHub activity, LinkedIn recommendations, etc. The same matching algorithm is also used to find the ideal jobs for good candidates.
A leading cloud security provider wanted us to detect anomalies and abnormal peaks in outbound traffic, using event logs. We set up a continuous feed of raw data logs, using AWS Kinesis rom AWS Cloud-Trail. Data was then grouped by Time, Usertype and Logtype into multiple batches. From these batches, variables were generated to feed in to the Machine Learning model which finally predicted if the data entry is an anomaly or not, using logistic regression.
When a world-famous manufacturer approached us with seven years’ worth of sales data and a vague need to make sense of it, we built them a platform that leverages Machine Learning to help improve sales through channel partners. Our models help them predict the probability of a quote turning into an order, and our ML algorithms make sure they never leave money on the table during bids.