Data Weaponization / ABMS Proposal

As per General Goldfein’s paper to the Air Force regarding Multi-Domain Command and Control (MDC2), the Air Force must be able to perform the form the following:   Situational Awareness - Collect and distribute data and transform it to intelligence. Rapid Decision Making - Use Situational Awareness to enable effective and timeline decision making at the right level, whether tactical, operational or strategic. Ability to direct forces to achieve commander’s intent - Leverage this enhanced decision making ability to direct forces across domains and missions. Splice Machine will greatly enable and improve these goals.  Splice Machine is a new, intelligent, scale-out SQL database that combines all of the computing needs required to power modern AI applications and systems on a pre-integrated/unified architecture (addressing Situational Awareness and Rapid Decision Making).  Some of the world’s largest Fortune 500 firms, including financial services companies, manufacturers, supply chain entities and retailers use Splice Machine to drive their businesses and making business decisions, as data volumes and data variety outpace traditional database technologies and the need for intelligence becomes central to their strategic goals.  Because Splice Machine is SQL-based, existing IT skills are maximized with lower risk, cost and time needed to migrate legacy applications or create new applications on Splice Machine. Splice Machine outperforms traditional databases by scaling to meet Big Data needs while infusing in-database machine learning. Unlike traditional Big Data architectures like Hadoop, we remove the complexity and data latency by engineering all the pieces needed to run at a Hadoop-like scale pre-integrated under the hood. The Air Force will also realize multiplied value in that it can run analytical workloads on the same data set without creating data marts or moving data to different analytical engines. Finally, our built-in machine learning libraries move data science from a backroom function to a core element of how real time decision making is done by removing the latency of data movement and providing data scientists tools to retrain and track data model/algorithm changes as their need for intelligence grows in the future.   Splice Machine can ingest both structured and unstructured data from multiple sources, in real time and in batch. This ability is paramount as Splice Machine can use this data as input to machine learning models who can provide predictions and recommendations directly in the database, to be used by our customers to make business decisions such as next best action, insurance claim fraud, recommendations to doctors on which prescription to provide to neurological patients, and more. Splice Machine is a member of C5 and SOSSEC.