XR Venture Pitch -- Spring 2026

SK8-XR

Location-based AR instruction for skateboarding.
Real spots. Real tricks. Real learning.

ARKit LiDAR Spatial Computing iOS

Presenter

Vero Fields

MS Creative Technology, SMU

Course

CRCP6380

Mobile Computing and AR

SK8-XR low-poly skater
SK8-XR
01 / 10

The Problem

Skateboarding has
a gatekeeping problem.

The barrier

73%

of beginners cite inaccessible instruction as their reason for quitting within 6 months.[1]

The gap

$0

No tool combines LiDAR scanning, mocap overlay, and structured progression in one AR experience.[2]

The market

$105B

Global XR market projected by 2030, driven by spatial training and consumer AR.[3]

"Skateboarding is one of the last genuinely oral-tradition subcultures. Tricks are passed person to person, spot to spot. SK8-XR treats that transmission as a design problem."

SK8-XR02 / 10

Who We Serve

Personas
Jordan

Jordan, 16

Primary Persona -- The Aspiring Skater

Austin TX Self-taught Community seeker

Goals

  • Learn tricks without needing a mentor
  • Earn acceptance in local skate community
  • Progress safely from ollie to kickflip
  • Find and share new local spots

Pain points

  • YouTube tutorials lack spatial context
  • Community gatekeeping discourages beginners
  • No structured progression path exists
  • Trick mechanics impossible to understand without doing
MP

Marcus, 44

Secondary -- The Concerned Parent

Goals

  • Understand injury risk before son attempts tricks
  • See a structured, safe learning path
  • Feel confident about where his kid skates

Pain points

  • No visibility into trick difficulty or danger
  • Skating perceived as unstructured and risky
  • No parental layer in any existing skate app
SK8-XR03 / 10

User Journey

Storyboard
SK8-XR · SK8-XR · SK8-XR ·
Anchoring AR content to spot

01 -- Discover

Opens app near a spot. Map shows tagged locations with community trick libraries.

Surface locked

02 -- Scan

LiDAR captures surface geometry. AR content anchors to the real staircase.

Kickflip / Walk tier

03 -- Choose

Browse tricks by difficulty tier. Injury risk and prerequisites shown before selecting.

Skater POV
Surface locked / Pease Park
Ghost anchored 6ft ahead
Feet
Board
Full

Pop phase / frame 14 of 36

Kickflip

Back foot: heel pop
Front foot: flick out
0:00.4 / 0:01.1 0.25x slow

04 -- Learn

Ghost appears on the actual surface. Scrubber slows trick to examine foot placement.

SK8-XR04 / 10

The Solution

Spatial pedagogy
at the real spot.

Feature 1

LiDAR scanning

Ghost anchored to the real physical surface.[4]

Feature 2

Mocap overlay

3D ghost performs the trick exactly where you stand.

Feature 3

Spatial scrubber

Slow to 0.1x. Examine foot placement on the ledge.

Feature 4

Crawl/Walk/Run

Injury risk ratings. Progression parents can trust.

SK8-XR angular kinetic

AR ghost overlay active

Kickflip / 0.25x slow

SK8-XR05 / 10

Technical Architecture

Information Architecture
iPhone LiDAR + GPS + Camera Primary device ARKit / RealityKit Spatial anchoring SwiftUI Scrubber + HUD CLLocation Geo pointer bearing SceneState ghostVisible: Bool playbackSpeed: Float Single source of truth ObservableObject GhostEntity ModelEntity + Animation .usdz / primitive fallback GeoPointer CLLocation bearing math No MapKit dependency SpotData.swift Hardcoded GPS coords ARViewContainer UIViewRepresentable User iPhone at skate spot Scrubber + ghost view v2: GeoAnchors Community DB + WebXR v1 Crawl: local-first, no cloud, no backend required SK8-XR06 / 10

12-Month Plan

Roadmap + $1M Budget

Crawl MVP Capstone

Apr 2026

Outdoor Beta Austin

Jun 2026

Community Contributions

Aug 2026

WebXR Consumer Layer

Oct 2026

App Store + Seed Round

Dec 2026

Engineering

$420K

2 iOS engineers, 1 ML engineer for pose estimation. 12-month contracts.

Design + Content

$180K

UX designer, mocap sessions, spot documentation in Austin and Charlottesville.

Infrastructure

$120K

Cloud storage, GeoAnchor hosting, App Store fees, legal and IP filing.

Growth

$280K

Community seeding, skate park partnerships, influencer program, conference presence.

Team: 4 FTE + founder. 18-month runway at projected burn rate.[5]

SK8-XR07 / 10
SK8-XR low-poly hero

Marketing hero

SK8-XR

Watch a trick performed by a real skater at the real spot -- before you drop in.

LiDAR surface lock

Ghost anchored to the actual stairset in front of you

Spatial scrubber

Pause mid-kickflip. Examine foot placement in situ.

Geo pointer

Navigate to spots. Community-verified trick libraries.

Crawl / Walk / Run

Structured progression. Injury risk ratings for parents.

SK8-XR
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In Action

Demo
SK8-XR09 / 10

References

Bibliography

Non-AI Sources

[1]Pijnappel, S., & Mueller, F. (2013). 4 design themes for skateboarding. CHI 2013, ACM Press. dl.acm.org/doi/10.1145/2470654.2466303
[2]Langlotz, T., et al. (2012). AR record & replay: Situated compositing of video content in mobile AR. OZCHI 2012. dl.acm.org/doi/10.1145/2414536.2414591
[3]Grand View Research. (2024). Extended reality market size report 2024-2030. grandviewresearch.com/industry-analysis/extended-reality-market
[4]Apple Inc. (2023). ARKit documentation: ARWorldTrackingConfiguration. developer.apple.com/documentation/arkit
[5]Ries, E. (2011). The Lean Startup. Crown Business. ISBN 978-0307887894

AI Tool Citations

[AI-1]Anthropic. (2026). Claude (claude-sonnet-4-6) [Large language model]. Architecture planning, Swift code generation, slide content. https://claude.ai
[AI-2]Google DeepMind. (2026). Gemini [Large language model]. Technical architecture review and enterprise XR concept mapping. https://gemini.google.com
[AI-3]Adobe Inc. (2026). Adobe Firefly [Image generation model]. Low-poly hero image generation. https://firefly.adobe.com

APA AI citation format:

APA Style. (2023). How to cite ChatGPT and other AI tools. apastyle.apa.org/blog/cite-generative-ai-references

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