Artificial Intelligence & Machine Learning

Our work model centers around the idea that the brain is composed of clearly distinguishable but interrelated and interconnected modules that self-assemble to solve problems using a harmonious system of local learning ("training or instruction") and innate knowledge ("education"). Our systems are designed in a similar fashion- they learn without explicit external guidance, becoming smarter and more self sufficient with every cycle. They provide advice and help humans in various real life ways, while still allowing the system to remain transparent and efficient.

Virtualinfocom's amalgamation of conventional numeric AI (machine learning, neural networks, and deep learning algorithms) plus advanced symbolic AI techniques (cognitive functions) enable our systems to scrutinize, reason, hypothesize, correlate, plan, acquire knowledge, and teach. The system produces clear, concise advice weighed and mapped out according to human expert knowledge and best practices. Our solutions are always aware of current scenarios, and this awareness helps them bring human-like reasoning to the table along with vast databases, helping them gain a competitive edge in diagnosing issues, forecast problems and suggest ways to resolve them.

Unlike conventional, clunky AI approaches, Virtualinfocom's cognitive AI solutions are always easily understood in mainstream terms and ideas, and can be interpreted directly by machines. Our subjective engines deliver transparent, well fleshed out audit trails explaining the logic behind their recommendations and showing the evidence, risk, confidence, and uncertainty. Our cognitive systems are experts in their own right, and give rise to operational efficiencies at a scale which in turn generates new revenue and increased profits. We have coined a new term for this advanced form of Return On Investment (ROI), RAI or Revenue from AI, since all of this is possible because of our groundbreaking AI technology.