STAR-T XR

We design product experiences where AI meets XR.

STAR-T XR is an immersive product surface for education, exhibition, culture, and collaboration scenarios, connecting AI docent flows, AR-first interaction, and operator tooling.

AR-first museum flow
Unity + backend + CMS structure
XR operator / analytics loop
XR Incheon full demo screen
Web Surface
XR Incheon Demo Surface

Source: xr_incheon

XR Incheon AI docent UI
AI Docent
XR Incheon AI Docent UI

Source: xr_incheon

Reference Scope
  • XR Agent Builder · MVP foundation
  • XR Museum MVP · AR-first experience
  • XR Incheon · Web surface foundation

What We Build

We prioritize XR systems that can be operated and extended, not just demo moments.

Education & Training

XR learning and training flows designed around what learners and field users can actually understand and use.

Exhibition & Museum

Story-driven museum and exhibition experiences such as artifact scan, reconstruction, and AI docent flows.

Collaboration & Spatial UX

Immersive collaboration experiences where communication and spatial interaction matter.

Operator-ready Surface

We design the operator surface too: content input, dashboards, event logs, and analytics.

GitHub Reference Backbone

These are the public XR repositories we can credibly use as the base of this surface.

MVP foundation

XR Agent Builder

AI-XR lifecycle engine for turning cultural, exhibition, tourism, and education content into reusable XR experiences.

An XR product skeleton with Unity runtime, backend/CMS contracts, builder tooling, event logging, and analytics loops.

UnityBackend APICMSAnalyticsPrompt Agents
AR-first experience

XR Museum MVP

Unity AI-XR museum MVP with AR scan, VR preview, AI docent, analytics, and backend services.

An AR-first museum MVP blueprint with a clear artifact scan, recognition, and XR reconstruction flow.

UnityAR FoundationFastAPIQuest 3 MRCurator CMS
Web surface foundation

XR Incheon

Next.js-based XR web surface foundation for an Incheon-focused experience layer.

A usable reference for quickly composing a dedicated web foundation for XR surfaces.

Next.jsApp RouterDocsPublic Assets

Field Snapshot

The visual layer also uses only assets that already exist inside the XR GitHub repositories.

XR Incheon full demo screen
Web Surface

XR Incheon Demo Surface

Source: xr_incheon

A full demo view from the Incheon XR web surface. The page visual tone is grounded in actual repository assets.

XR Incheon AI docent UI
AI Docent

XR Incheon AI Docent UI

Source: xr_incheon

A reference image showing the AI docent interaction and UI layer inside an XR experience.

XR Incheon AR scene
AR Scene

XR Incheon AR Scene

Source: xr_incheon

A visual reference for AR scene direction and spatial storytelling in field-based experiences.

How We Deliver

01

Scenario Definition

We first lock the user and operator scenarios: who experiences what, in which space, and in which moment.

02

Prototype & Pilot

We compress Unity, AR/MR flows, and backend contracts into a pilot-ready prototype quickly.

03

Operate & Measure

We extend into content operations, event logging, curator/operator workflow, and analytics.

Capability Surface

Unity Runtime
AR Foundation
Meta Quest / MR Track
FastAPI / Backend Contract
Operator CMS
Event Logging / Analytics
AI Docent / Builder Flow

If you want XR to become an operable product rather than a one-off demo

Our current public references already span a product skeleton, an AR museum MVP, and a dedicated XR web surface foundation. Once the scope is clear, we can help define the path from PoC to pilot operations.