Data and AI

Data Discovery

The most important step in any data undertaking is to define the problem at hand. This involves understanding the business objectives from various stakeholders. We then identify the right data sources based on business objectives. Often data in large organizations exists in silos. Once the sources are identified, the data needs to be processed: cleaned and transformed into a standard format.

Data Exploration and Visualization

A key step once the right data is in place is to visualize it. Charts and graphs are used to present complex data in a way that is easy to understand. Statistical methods are employed to create summaries that serve as a high-level overview and a starting point for exploring the data at a more granular level. In many cases, this dashboard would be of great value to the business showing trends, outliers and giving the stakeholders insights that are driven by data.

AI

Statistical techniques can create business reports. More often, the problem at hand involves predictions and classifications based on the current data. Depending on the problem at hand, we identify the relevant features in the data, we select the most appropriate learning algorithms and then create a model that learns from your data. Our expertise spans everything from Regression Models, Decision Trees, Support Vector Machines, Convolutional Neural Networks, LLMs and more. Once the model is trained and evaluated, we ensure that it can be integrated into production systems and scale efficiently.