State-of-the-Art Machine Learning Software for Mission Critical Results
Government agencies are tasked with the challenge of providing citizens with more efficient, effective, and transparent services with strict and often decreasing budgets. Government agencies can use machine learning to increase operational efficiencies by analyzing datasets, finding patterns and anomalies, and making predictions about future events.
Skytree’s state-of-the art machine learning software can analyze both structured and unstructured data sets in real-time to produce fast, accurate and scalable results that are up to 10,000 times faster than previous approaches. Skytree comes with a breadth of advanced machine learning methods that utilize the research available to you to make predictions with the highest accuracy available, far surpassing what’s possible with basic analytics.
Skytree can help government organizations:
Detect and prevent fraudulent transactions, accounts and vendors. Constant improvement of fraud detection capabilities is crucial to addressing rapidly shifting fraud scenarios. Compared to legacy solutions, Skytree can incorporate and analyze more data across multiple channels, such as point-of-sales, web and mobile to yield faster, real-time fraud analytics and forensics.
Identify anomalies or signatures to address proliferation, terrorism, money laundering, counterfeit devices, threats and other criminal activity. Leverage your data assets to make informed decisions and detect suspicious activity before it’s too late.
Bring Relevant Content to the Analyst or IT user – Smarter than Smart Search
Identify important information, trends and triggers to highlight the most relevant and high impact information. Skytree provides customized views of complex data, refocusing attention onto areas of relevance in relation to the problem at hand, as well as providing the opportunity to incorporate user feedback without setting hard rules that create permanent knowledge holes moving forward.
Other Applications of Machine Learning in Government Agencies
Cybersecurity. Identify abnormal activity, correlated nefarious patterns across multiple data types and inputs, and prescribe actions based on all the factors. Examples include insider threat, network design/operations, threat detection/alerting and software defined networking.
Situational Profiling. Based on the information at hand, identify what is important and where to look. Customized view of complex data. Examples include risk heat map, identity intelligence, activity based intelligence (ABI)/object based production (OBP) and event/activity prediction.
Pattern of Life. Identify trends and correlations among different groups to detect various subtle and complex patterns. Gain a deep customization of response, based on a thorough understanding of the players involved.