Civilise.ai aims to redefine urban development by using AI & Computer Vision to to design cities/suburbs. Our objective is to address the issue of housing affordability & rapid urbanisation by reducing the cost associated with a suburb planning design for governments and private land developers.
Civilise.ai aims to redefine urban development by using AI & Computer Vision to to design cities/suburbs. Our objective is to address the issue of housing affordability & rapid urbanisation by reducing the cost of a suburb planning model for governments and private land developers.
Currently, we are developing our system, Oak, to incorporate current metrics & regulations to assess and design suburbs. This will allow for past suburbs to be scored & for future suburbs to be automatically generated in relation to those positive metrics. Consequently, this reduces months of urban planning for state governments & private land developers while also allowing multiple iterations in a short period of time.
Our customer segments are state governments, local councils and private land developers.
After engaging with the Suburban Land Agency & two private land developers, we've gain insights on various metrics that would be attractive in a suburb planning. One such metrics which we are currently developing for our stakeholders is walkability (how walkable to commercial districts, schools, public transit).
Currently for a suburb development process, the state government or land developer will usually engage multiple different consultants (geospatial, urban , flood management , design etc etc) to effectively work on a model. Although it gets the job done, it is essentially a time consuming & expensive process.
We are redefining the process using machine learning to autonomously generate a suburb design with the desirable metrics and past suburbs designs that has already been incorporated in the AI model.