KERNELBAY

Kernelbay completed a project for an IT Services Company where they were tasked with creating a Machine Learning (ML) model to predict consumer behavior and prescribe sales strategies accordingly. The vendor's team, which comprised of a data engineer and two ML engineers, enriched a large dataset of sales data with a wide range of environmental parameters. The data was then analyzed to find correlations, patterns, and anomalies, which were used to build the ML model. The client was impressed with Kernelbay's ability to quickly understand their vision and deliver a ready-to-use augmented analytics solution.

In another project, Kernelbay worked with a software company that develops a cloud platform for crop monitoring. The company's CEO wanted to improve the accuracy of their crop loss prediction model. Kernelbay suggested enriching the vegetation activity data with parameters like temperature, wind strength, soil moisture, and atmospheric pressure. A team from Kernelbay, consisting of a data analyst, data engineer, and data scientist, worked on this project. They retrieved synthetic data from images, enriched it with environmental data, and applied ML algorithms and statistical methods to develop a forecasting service. The client commended Kernelbay for their innovative approach and the significant improvement in results.