Sep 11, 2026 · 48 min · 14 segments
There's no magic scan-to-BIM button. This episode covers reality capture, digital twins and where AI actually helps turn scans into decisions. Reality capture has quietly moved from a specialist…
Dominique PouliquenGuestAndrea CiaffiHost
So the core technology we got from my co-founders, PhDs, was this capacity to turn a huge point cloud into compressed data.

So by turning point cloud into 3D surfaces, I was also pretty convinced that this would be a much easier way to interpret your point cloud data.

Secondly, the 3D surface you get or the 3D mesh you get will make the data much easier to view and interpret.

And last but not least, the core technology also includes the fact that we can stream these high resolution 3d meshes which are at the resolution of the source scan in a web browser using fast streaming so people at that time were calling us oh you are the net you are the netflix for 3d data because we could stream high resolution 3d meshes in a web browser okay that was really cool and the technology is so advanced that once we turn a point card into a mesh we can do the inverse transformation, mesh back to the source point cloud with no loss of data.

And that's really interesting because in some use cases, when you need to have your reality capture data in Revit for scan to BIM, you need a point cloud.

Because what we did with the recap team at that time, with the Revit team, by putting the recap engine into Revit, you would be able to snap primitives of Revit to the point cloud so you need point cloud in revit okay now it's kind of changing now people can use meshes also in revit so but that was a that was the initial value proposition we had with cinto okay so uh compression we could compress the data 20 times okay so from 20 to 1 we could upload then the data to the cloud we could stream very fast and we could view these beautiful meshes in a web browser or we could turn back the machine to point cloud when you needed the data back in Revit.

So the core technology we got from my co-founders, PhDs, was this capacity to turn a huge point cloud into compressed data.

So by turning point cloud into 3D surfaces, I was also pretty convinced that this would be a much easier way to interpret your point cloud data.

Secondly, the 3D surface you get or the 3D mesh you get will make the data much easier to view and interpret.

And last but not least, the core technology also includes the fact that we can stream these high resolution 3d meshes which are at the resolution of the source scan in a web browser using fast streaming so people at that time were calling us oh you are the net you are the netflix for 3d data because we could stream high resolution 3d meshes in a web browser okay that was really cool and the technology is so advanced that once we turn a point card into a mesh we can do the inverse transformation, mesh back to the source point cloud with no loss of data.

And that's really interesting because in some use cases, when you need to have your reality capture data in Revit for scan to BIM, you need a point cloud.

Because what we did with the recap team at that time, with the Revit team, by putting the recap engine into Revit, you would be able to snap primitives of Revit to the point cloud so you need point cloud in revit okay now it's kind of changing now people can use meshes also in revit so but that was a that was the initial value proposition we had with cinto okay so uh compression we could compress the data 20 times okay so from 20 to 1 we could upload then the data to the cloud we could stream very fast and we could view these beautiful meshes in a web browser or we could turn back the machine to point cloud when you needed the data back in Revit.
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