It is a tool that experiment in how a company can work, and see how much a fully distributed system is able to solve problems efficently. This project uses soft computing, on the opposite of hard computing, the terms "soft computing" and "hard computing" refer to two different approaches to problem solving.

Hard computing, also known as "classical computing," refers to the use of traditional, precise algorithms to solve problems. It relies on strict rules and precise calculations, and it is well-suited to tasks that require a high level of accuracy. Hard computing approaches are often used in scientific and engineering applications, where the stakes are high and it is important to have reliable, precise results.

Soft computing, on the other hand, is a term that encompasses a range of techniques that are less precise and more flexible than hard computing approaches. It includes techniques such as artificial neural networks, fuzzy logic, and genetic algorithms, which are inspired by natural processes and are designed to be more tolerant of uncertainty and imprecision. Soft computing approaches are often used in situations where it is more important to find a satisfactory solution than to find the optimal solution, or where the data or problem characteristics are too complex or uncertain to be solved using traditional methods.