Enable faster decision-making and analysis by automating data preparation of operational data

Sentenai proposes to adapt it's commercial product offering to help solve data preparation problems within the Air Force for a variety of data analytic applications. Sentenai's proven commercial solution is a data fusion and decision support system that automates the data engineering processes required to unify operational data under a single, optimized virtual context, ready to be used for interactive analysis by end-users to make realtime decisions based on analyses performed across thousands of data sources simultaneously. Sentenai addresses the challenge with variety in big data — in complex operational environments, there are a large number of data sources, decision-makers are continuously forced to make tradeoffs between making a decision based on analysis of all the data and making a fast decision based on only a small amount of the data. Sentenai takes an automated approach to addressing the data engineering challenge of combining thousands of disparate data sources to perform comprehensive, interactive analysis of data. Sentenai is an open, modular system that works well in existing environments, whether in the cloud (AWS, GCP, VMWare, etc) or on premise. In addition to providing support for a broad number of data interchange standards and SDKs for common programming languages (e.g. Python, R), Sentenai also provides standalone interfaces for historical data analysis, multi-source pattern matching and time series visualization.