RembrandtA is a transactional multi-layer artificial intelligence solution. It is a culmination of decades of technological
progress in the field of
artificial intelligence. That evolution did not follow a straight line, but was a development of different dimensions in this fascinating field.
RembrandtA layers the best of those AI developments into a comprehensive, ground breaking system. When it comes to solving
business problems, one
does not fit all. Some problems can be solved by simply presenting raw data in a helpful and meaningful format, so that a human analyst can see the
answer by just looking at it. Other problems can be solved with the help of classical statistical analysis, which includes trends, summaries,
etc. If the patterns of discovery can be defined, then the expert system approach has proven itself as the fastest and most reliable way to
conditions. In addition to speed and reliability, the fact that the rules that were used for the solution are understandable provides a level of
communication not available with neural nets. A machine-learning layer is often effective on top of expert systems, to mimic a user's natural
distinguish between true positive and false positive results produced by the expert system layer. Higher layers of the system add the ability to
discover and detect behavior and profile deviations, and not yet described conditions.
Experience has shown that real-life problems are best solved by judicial combination of several types of AI with tools that enhance the abilities of
human beings to think and act. RembrandtA solutions use expert systems for their speed; artificial neural nets for their machine
model management tools for model evolution. RembrandtA also adds extensive data visualization and informative alerting, so that
human beings can do
their jobs and make informed decisions effectively. RembrandtA effectively combines artificial and natural intelligence: it values
the abilities of
human experts, who were the inspiration for expert systems; it values the ability of people's brains to recognize situations when they see them,
was the inspiration for artificial neural nets.