The creation of a positioning system has use cases for indoor, outdoor and even small-scale deployments. These solutions often use a broad range of technologies and algorithms that each have their advantages as well as limitations. Existing open source positioning solutions often offer a complete package for indoor navigation or asset tracking that allows developers to set up a specific application with minimal effort. However, these positioning solutions offer little room for developers to customise them. OpenHPS is an open source hybrid positioning framework for creating a positioning system without being bound to a specific technology or a set of algorithms. Developers are free to choose the data they want to use, from where they want to obtain this data, how to process the data and finally how to use the outcome of the positioning system. In this presentation we will present the modularity and ecosystem around the OpenHPS framework, some technical aspects as well as the current state of the project. A localisation system often has use cases such as tracking employees or navigating people at a conference. When looking at the problem in a more broader perspective the use cases often span way beyond the tracking and navigation of people. Whether it is a use case where pawns need to be tracked on chessboard or a robot needs to navigate itself outside and through multiple buildings, different approaches need to be used.