With the endless list of building codes specific to different areas nowadays, building homes and buildings can be a really stressful job. Something that is perfectly legal in one area of the city would no more be legal in the neighbouring area. The stark contrasts in the building codes to adhere to makes home building just that much more painstaking especially when into take into account their never-ending code-books.
The guidelines given in the code-books are given to help protect the constructed homes from various threats such as weather, local terrain, climates and various other risks. While this is in place for safety, the benefits come at the heavy cost of convoluted rules which ultimately drive up the price for building homes by a factor of multiples. All that, just to understand the certain requirements for building a home in a specific area.
That’s where Machine Learning based startups like Cover, Cove.tool and more are having their platforms run advanced scenario-analysis around interweaving building codes and inter-dependent structural variables. This ultimately allowing users to create compliant designs and regulatory-informed decisions without having to ever encounter the regulations themselves and ultimately saving up a lot on expensive consultancies.
Cover helps the users decide what kind of backyard homes can be designed created for their properties. On the other hand, Cove.tool analyzes local building energy codes and determines the most cost and energy efficient resource mix to adhere to local energy requirements using location services. Similarly, Cover and Camino are helping steer home and business-owners through arduous and analogous permitting processes.
While the rules are certainly in place for a reason, they are so interwoven and specifically placed that it is quite a mess to take care of them. Especially with heavy fines being levied for not adhering to the code-book. Hence, startups like these are more than necessary at this point in time to not only make building homes easier but also to help reduce the costs of expensive counselling sessions and make the process faster as a whole.