VisionGuide
An AI-powered visual assistant that lets customers use their phone cameras to identify hardware issues — with AR-guided solutions delivered in real time.
Camera → recognition → guidance
Customer points camera
At their hardware — appliance, machine, equipment.
AI recognises the issue
Computer vision identifies the product, component, and problem.
AR guides the solution
Step-by-step visual overlay shows exactly what to do.
What teams see after deploying
Serving multiple departments
Visual self-service
Reduces support tickets. Customers resolve issues without calling — AI handles first-line diagnostics through the camera.
Interactive product experiences
Drive engagement with prospects. They explore features through their camera with overlaid specifications and comparisons.
AR-guided workflows that stick
New technicians learn by doing — guided step-by-step through real equipment with visual overlays.
Camera-based defect detection
Integrated into QA workflows. Consistent inspection standards enforced through AI vision, not human judgement alone.
Three production demos
Real deployments shipped to users. Click a tab.
Acer laptop repair walkthrough
Phone camera scans the laptop; AI identifies components; AR overlay guides the repair step by step.
Canon printer setup on Meta Quest
Headset camera recognises the printer in front of the user; step-by-step overlay drives an assisted setup.
LED status detection on printer
Phone camera reads LED state from the device; the AR UI reacts to the detected fault condition.
Technology we used
Vision & AI
- Object recognition
- AR rendering
- 3D mapping
- Real-time inference
Platforms
- iOS · ARKit
- Android · ARCore
- XR headsets · Meta Quest
- Web · Three.js
Infrastructure
- Cloud ML pipeline
- Edge inference
- Real-time streaming
- API layer
Need something similar?
We built VisionGuide from scratch — concept to production. We can do the same for your use case.