Artificial Intelligence & Machine Learning

Our philosophy centers around the idea that the brain is composed of distinct (but interacting) modules that self-organize to solve problems using a complement of local learning ("training") and innate knowledge ("education"). In this way, our systems are designed to learn autonomously, and become smarter with every cycle, in order to provide transparent guidance that assists humans in making better decisions.

Virtualinfocom's hybrid of conventional numeric AI (machine learning, neural networks, and deep learning) plus advanced symbolic AI techniques enable our systems to analyze, reason, hypothesize, correlate, plan, learn, and teach. The system produces clear advice weighed according to human expert knowledge and best practices. On top of comprehending vast amounts of data, our solutions bring situational awareness plus human-like reasoning to diagnosing issues, prognosticating problems, and suggesting remedies.
In contrast to conventional AI approaches, virtualinfocom's cognitive AI solutions are always "explainable". Our cognitive engines deliver transparent audit trails explaining the reasoning behind their recommendations and showing the evidence, risk, confidence, and uncertainty. These audit trails are designed to be understood by people and interpretable by machines. We build cognitive systems that think like experts and produce operational efficiencies at scale that equate to new revenue and increased profits. We have a new term for this new form of ROI generated by AI: "RAI" or Revenue from AI.