BLOCKCHAIN & AI

AR/VR Experiences

Build immersive demonstrations, training and interactive experiences shaped around real devices and measurable user tasks.

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Overview

We design augmented and virtual reality experiences for practical situations, from product exploration to scenario-based learning. The choice between browser delivery, mobile AR and dedicated headsets follows audience needs rather than novelty.

Projects combine interaction design, asset optimisation and device-specific implementation. We consider physical surroundings, motion comfort and alternative ways to access important information, alongside consent and retention choices for any spatial or behavioural data collected.

What We Build

AR product viewers

Place supported digital models in a user’s surroundings with appropriate scale cues.

VR simulations

Create guided scenarios with structured interactions and feedback tied to learning objectives.

Immersive demonstrations

Build navigable experiences for exhibitions, sales conversations or remote product exploration.

Key Features

Comfort options

Consider locomotion choices, session length and alternatives to demanding interactions.

Optimised assets

Balance texture detail, geometry and loading against target device limits.

Selective measurement

Collect agreed interaction metrics without assuming continuous recording is necessary.

Our Process

  1. Discovery

    Identify user tasks, deployment settings and available hardware.

  2. Design

    Prototype interactions and assess comfort with representative participants.

  3. Development

    Develop scenes, input handling and any required platform integrations.

  4. Testing & Security Audit

    Test tracking, frame performance, accessibility options and data permissions.

  5. Launch & Support

    Package releases and agree device compatibility and content update support.

Tech Stack

  • Unity
  • Unreal Engine
  • WebXR
  • ARKit
  • ARCore

Frequently Asked Questions

Can an existing model be reused?

Often, but engineering models may need substantial optimisation and material adjustments.

Will it work on every headset?

No. Supported devices and operating versions are agreed and tested explicitly.

Can training outcomes be measured?

We can capture defined task indicators; claims about learning improvement require appropriate evaluation.

Is camera footage stored?

Only where required and agreed; permissions, processing and retention need explicit design decisions.

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