We perform thousands of simulations and use machine learning techniques along with custom data visualization tools to facilitate multi-criteria decision making and help design team meet their energy and environmental goals while keeping check on the first cost and other constraints. We evaluate a large number of parameters and their combination in order to provide enormous flexibility where we start with screening of parameters, followed by exhaustive combinatorial simulations and machine learning techniques.
Our principle objective is to provide a tool in the hands of the design team to make decisions that suit them best rather than us dictating the limits on the parameters and decision criteria. The tools can be imagined to have both forward feed and back propagation capabilities that can be used with the end in mind.
The methodology and work flow is designed to help at all stages of design starting from Conceptual Design through Schematic, DD, CD phases including value engineering with LCC approach.
