Recently, immersogeometric analysis (IMGA) was successfully applied to simulate compressibleand incompressible fluid flows over CAD models represented using triangles, non-uniform rational B-splines (NURBS), and analytic surfaces. However, performing flow analysis over real-life objects requires CAD model reconstruction, which can be as tedious as the mesh generation process itself. In a point cloud geometry, the object is represented as an unstructured collection of points. Point cloud representation has proliferated as a form of acquiring geometric information in digital format using LIDAR scanners, optical scanners, or other passive methods like multi-view stereo images. In this work, we perform IMGA directly on point cloud representation of geometry, thus enabling flow analysis over as-manufactured components. Due to the absence of topological information in a point cloud, there are no guarantees that the geometric representation is watertight, which makes performing inside-outside tests on the background mesh challenging. To address this, we first develop methods for generating topological properties on a point cloud and compute inside- outside information directly from the resulting topology. Then, validations are performed for these geometric estimation methods, as well as for point cloud IMGA (PC-IMGA) incompressible flow results. We finally demonstrate additional features and scalability of our approach by performing PC-IMGA on large construction machinery represented by a dense cloud of more than 12 million points, along with our other PC-IMGA developments, including weak thermal boundary conditions and transient boundaries.