Innovative Science and Technology Solutions

Augmented Reality

RWISE makes unique use of 21st-century data sciences and technologies to give users unparalleled insights of their world today and provide forecasts of tomorrow. Data sets from any realm of interest can be ingested into RWISE, creating a synthetic model from which you can run simulations by baselining the past and projecting trends forward. RWISE is the product of 20 years of progression in modeling and simulation, and agent-based modeling started with its predecessor platform known as Synthetic Environment for Analysis and Simulation (SEAS) Virtual International System (VIS). SEAS VIS and RWISE have been used by the U.S. Government, NATO, other countries, State, County, and City governments, Non-Profit.

Quantum Computing

Our quantum computing solutions can help you solve problems that are impossible for classical computers, improve security, and advance research in science and technology. Let us help you explore the possibilities of quantum computing.

Applying advanced technologies for performing data analytics

Reference World – Information Synthetic Environment v 4.0 (Reference World or RWISE) is a Data Science/ Machine Learning/Artificial Intelligence (DS/ML/AI) driven Modeling & Simulation as a Service (MSaaS). It has been used to model societal structures, networks, social nuances, and behaviors to simulate different decision effects on different segments of society. RWISE’s M&S capability consists of three major components; 1) a “current state,” data lake that’s derived from the DSML ingested historical and real-time data which is made available for cross-domain analytics, 2) an integrated synthetic model bounded into a societal architecture with unique Artificial Intelligence methods, and, 3) an agent-based simulation engine that first creates a baseline forecast of the “future state” then is used to test potential policy actions for future effects to compare to the baseline. The “agents” may respond behaviorally to changes in their environment and may prompt changes within their networks during simulations. This is based on Nobel winner Daniel Kahneman’s Wellbeing Theory.

Dynamic data streams illustrate RWISE’s advanced AI and machine learning simulation environment.

The Algorithms

RWISE integrates advanced algorithms for predictive modeling.

Our advantage over other solutions

We design our analytics using multiple AI processes. methods including Boosted Decision Trees, Logistics Regression, and Gradient Descent are part of our workflows.

No one else integrates at the level of sophistication like RWISE does.

Creating a baseline
The RWISE simulation engine can carry historical trends forward to create a baseline future. You can then insert different actions to see their likely future impact.