Contributed by: Maia Mongado


ProspectVR is a collaborative VR app mainly targeted at displaying large scale models of homes and buildings for business purposes. However, its general framework and its ability to handle large, complex models makes it particularly well suited for various types of data visualization. Users can share files, share space, see, hear each other, and view the same models in real time. In addition, they have access to a shared file space.

There is a different version for guests that includes a simpler onboarding process, making leader / guest capabilities quite streamlined.

It is primarily a paid app and has limited free versions you can request for demo purposes.

There is a fair amount of current development going on and there are various plugins; they are under the larger branch company of IrisVR, which maintains a blog and documentation for how to use Prospect.

Supported files for importing: Navisworks, Revit, SketchUp, Rhino, OBJ, FBX, IFC
For more info on importing specific files (as many are indirectly importable), check
this page.

VR Requirements

VR Setup

1.) Prospect is primarily a paid app, but for a free demo version you can sign up on their website here.

2.) You will receive an email with a download that is compatible with PC headsets; I would recommend downloading onto a PaperSpace machine, where you can open the download.

4.) Connect your headset using Virtual Desktop and the app should be launched automatically.

3.) Alternatively, you can download their Oculus Quest version through the App Lab - this is significantly buggier but more streamlined.


Accessibility: The estimated time for someone to get it up and running

  • Availability - Somewhat complicated setup - requires an outside download (not through Oculus or Steam) and a PC connected headset, and then setting up an account with IrisVR / Prospect. It is also primarily a paid app ranging from 225-350 a month (with other custom prices for custom capabilities; you can get a free version for 2 weeks.

  • Ease of use - There is a short and easy opening tutorial that you can do to get accustomed to the controls. Movement was noted as especially intuitive.

Power: The engine's power - i.e. how much one can do with this

  • Medium: The data visualization is fluid and well supported, but it doesn’t provide much ability to change existing meshes.

Usage: Evaluation of software's use for the following purposes

  • Art / Game Design - Unlike ShapesXR, doesn’t have the ability to move through different work spaces - especially powerful and meant to handle large meshes, so would be great for scene design.

  • Science - Good for observing existing .obj files and could be useful for things like chemistry where 3D shape is extremely important. However, there's not much ability to change / edit shapes and meshes.

  • Education - The set up process is a bit complicated but the controls are fairly easy to use. Moreover, there is a simple Guest login for people who just want to view a model led by a leader; this is especially useful for educational purposes.

Collaboration Evaluation

Avatar representation

  • Users noted that the avatar representation was well done - it showed head and hands position, as well as a name above each head, and a different color for each avatar. However, it was not so detailed as to be distracting - it captured the key parts of each person. There was also a laser pointer ability not present in some other apps that proved to be very useful.

Communication ability

  • There is spatial audio in the app, which is the primary mode of communication between avatars. There is also guest / leader capabilities, with lasers indicating where users are pointing and the ability to gather or go to certain users. There is not much ability to communicate in a written fashion, which users noted would have been useful for message persistence.

Shared workspace

  • Users were able to explore a model together and point out different parts, thanks to the leader / follower ability and the laser pointer ability. There is also file sharing between all users, so outside of just a collaborative space there is also data sharing. However, the space isn’t meant so much for changing models as much as it is for exploring large models, so there isn’t much ability to “work” together in that sense