In 2007, only two years after its founding, Ontonix has been selected Cool Vendor by Gartner. Below is full text of Gartner’s analysis by Marc Halpern:
“Analysis by Marc Halpern, Gartner
Why Cool: Ontonix has vision and software that go well beyond the mainstream of today’s computer-assisted analysis and simulation software. The software can identify critical variables and their relationships by processing computer generated data, measured data from real systems, or a combination of different types of data. It provides insight into making systems more reliable without compromising functions. Gartner is not aware of other software that can quantify the vulnerability of a process or a system in a rational and comprehensive manner that relates to system complexity and how uncertainty impacts those systems. By enabling manufacturers to use complexity as a design attribute, they can reduce complexity without compromising function,
thus making the systems more robust. The technology has been applied to computer-aided design, illustrating how it is possible to design components so they are as simple as possible, while guaranteeing the desired performance. The software can also be applied outside manufacturing. For example, Ontonix’s approach has been used to assess nuclear power plants and has strong potential for air traffic monitoring and evaluating investment strategies. In contrast,
the mainstream of today’s software predicts and simulates system behavior using deterministic methods that ignore the various unpredictable events that systems often encounter. While leading-edge mainstream software enables some stochastic simulation, it lacks Ontonix’s ability to evaluate the nature of the relationships among critical variables and provide insight into how those variables interact. Ontonix offers its analysis of system complexity as a secure on-demand service. The complete licensed software gives more detail and guidance toward analyzing system vulnerability.
Challenges: This company needs to focus attention on educating the market, publicizing the validation points and educating the technical community. Effective use requires grounding in probabilistic mathematics and complexity science, which underpin the approach. Systems-centric thinking is also essential for success. Mainstream engineers and other technical specialists are not facile with these skills. Therefore, the mainstream’s lack of relevant technical orientation poses further challenges to communicating the value of this technology. Also, even though the technology can yield superior designs, regulatory bodies unfamiliar with the approaches will question design decisions that Ontonix can influence.
Who Should Care: Manufacturers of complex highly engineered systems are top candidates for such software. Devastating consequences of system failures motivate top prospects to adopt this technology. Early adopters and most likely customers come from the automotive, aerospace and nuclear power industries. Engineering managers supported by deep technical specialists should be the decision makers. CTOs should be aware of this technology.”
Below are some of the early examples of Quantitative Complexity Management in Engineering.
Artificial Intuition 
Great! I see you are all out pushing QCM brand. Best, Mike
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