Interview· 1 h 21 min
From 3D scans to indoor navigation and tracking – Nikhil Sawlani, MultiSet AI
Listen to the audio
Summary
Nikhil Sawlani, founder of MultiSet AI, shows how reality capture professionals can reuse already-scanned spaces for live services: visual indoor positioning, 6DoF tracking, asset navigation, AR work instructions and robot-ready maps – an upsell from data many teams already have.
Key ideas
- 1GPS fails indoors and beacons need hardware; visual positioning works from existing scans.
- 2Scans from iPhone LiDAR, Matterport, NavVis, Leica or XGRIDS can become machine-readable maps.
- 3Confidence scores and map versioning handle changing environments and crowds.
- 4Navigation is a clear upsell for scan-to-BIM and industrial facility projects.
Chapters
Full show notes
I am speaking to Nikhil Sawlani, founder of MultisetAI.Instead of delivering only a static point cloud or 3D mesh, reality capture professionals can reuse already-scanned spaces to create live digital twin services: indoor positioning, 6DoF tracking, asset navigation, connected worker workflows, smart glasses guidance, no-code AR instructions and robot-ready spatial maps.We cover how Multiset AI works, why GPS and Bluetooth beacons fail indoors, what scan data is required, how confidence scoring and map versioning handle changing environments, and where the clearest upsell opportunities are for scan-to-BIM, industrial facilities, shopping malls, factories and enterprise digital twin teams.Chapters00:00:00 Are reality capture companies leaving money on the table?00:01:00 Point clouds vs real digital twins00:02:38 Upselling already captured scan data00:04:05 360 video, SLAM, LiDAR and scan quality00:07:03 What Multiset AI actually does00:09:10 Why GPS and GNSS fail indoors00:11:57 Bluetooth beacons, Wi-Fi and UWB limitations00:17:23 Hardware-free visual positioning systems00:19:18 5–10 cm indoor accuracy and 6DoF tracking00:23:40 How VPS matches camera views to 3D scans00:27:01 Turning massive point clouds into machine-readable maps00:30:46 Handling changing environments and crowds00:34:01 Confidence scores, sensor fusion and accuracy control00:41:54 AR navigation, overlays and device tracking00:44:39 Supported scanners, maps and file formats00:48:30 Panoramas, point clouds and E57 requirements00:53:37 Business case: upselling navigation from existing scans00:57:53 AR work instructions and connected worker use cases00:59:54 AI agents for factory asset navigation01:03:18 Mapping with iPhone LiDAR, Matterport, NavVis, Leica and XGRIDS01:07:07 Gaussian splats, metric scale and VPS localization01:13:11 Robotics, physical AI and one spatial source of truth01:15:36 Smart glasses navigation with Meta Ray-Bans01:17:32 Onboarding, free tier, SDKs and no-code options01:19:50 Final advice for reality capture professionals
Related
1 h 57 minInterview
The world is becoming a digital twin – Bilawal Sidhu on AI, OSINT and spatial computing
Bilawal Sidhu
1 h 31 minInterview
The future of 3D scanning is autonomous – Ben Williams, Exyn Technologies
Ben Williams · Exyn Technologies
1 h 43 min