What We Do

We use data science and machine learning to discover data patterns and create data models to help make more accurate predictions, uncover hidden themes in large data collections, curate them, deal with missing information and create advanced analytics solutions.

Data Science

Apply advanced analytics solutions using techniques such as data/text mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, sentiment analysis, network, and cluster analysis. Engage multivariate statistics, graph analysis, simulation, and complex event processing. Implement models in machine learning, optimization, neural networks, and artificial intelligence such as natural language, transfer learning, deep learning, and other quantitative approaches.

Machine Learning

Enhance data self-service abilities by intelligently recommending data sets that might be of interest, suggesting next-best-actions or automatically associating business terms and definitions with the underlying technical data. Identify master, reference, and transactional data domains such as people, orders, and leads and automatically infer similar data from user tags to discover relationships among data.

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