Core Technologies

Computer Vision

A.I.

Spatial Computing

Digital Twins

Computer Vision AI Integrations and Capabilities

Machine Learning, Models, AI On Device Integrations: Apple CoreML, Google ML, Open Source Models, UltraLytics, Meta Vision Models, OpenAI.

Capabilities: Object Detection, Body Tracking, Body and Pose Tracking, NSFW Visual Safety, Segmentation, Background Removal, Zero Shot Classification, YOLO, Text and Barcode recognition

Roadmap: Partner Vision Models for Dermatology Feature Detection, Medical Equipment Inventory detection, Hand tracking

Spatial Computing Technologies

iOS, iPhone, iPad

ARKit, RealityKit

OpenUSD, Reality Files

Multi Model Support

Authoring Enabled In Spatial Computing Stage (No Unity Dependency)

Augmented Reality support for Images, Video, Text, 360 Video, Holograms, Spatial Audio, Digital Twins and Interactive Models

Lidar Measurement Tools

Local, Remote Cloud Galleries

iCloud, Google Drive, Photo Gallery, Google Cloud, Firebase

Generative AI Assets

Roadmap: NVidia Omniverse Drive Integration, NVidia Deep Search, NVidia Omniverse APIs, Digital Twins with AI integrations, Environmental models using Neural Radiance Fields, Vision based surface detection, Advanced Anchoring

Computer Vision Cloud AI Integrations

Landing Lens, Open AI, Google Vision

Roadmap pipeline: Roboflow, NVidia Vision Pipelines, Google Gemma, Microsoft Health and Computer Vision, Enterprise Computer Vision Models

Generative AI XR Integrations

GenAI: OpenAI

Roadmap: OpenAI Sora (Video), Stability AI (3D Generation), Luma (Nerf GenAI), Luma Genie (3d), OpenAI GPT Vision (Multi-modal XRxAI)
NVidia Nemo, Picasso, Omniverse NIM Pipelines, Multi-modal chaining pipelines

FOCUS AND PRIORITISATION

Mobile Hardware Not Goggles

Mixed Reality Not Virtual Reality

Mobile Spatial Computing Interfaces Not Cloud

Look through the App Not at the App

Train On the Field Not in Seminars

Workers on the move Not Tethered to the desk