VR games

Vermillion – VR Painting

Educational game development case study

Educational example — not a CrocoApps project. This page analyzes a third-party product and presents an illustrative plan for a different, original project. No client relationship, development credit or endorsement is claimed.

Vermillion – VR Painting provides a useful reference for vr / simulation. The exercise below considers how a team could explore a spatial creative tool whose output can survive outside the VR session.

Reference product: verified public facts

A VR painting application with brush-based creation and export features. Steam also describes shared painting sessions and lists SteamVR/OpenXR-related requirements.

Source: Official product listing / project site. Reviewed October 21, 2026.

Project snapshot

Reference productVermillion – VR Painting
Developer / seller attributionThomas van den Berge (listed developer)
ClientNo CrocoApps client: third-party educational reference.
CountryOriginal commissioning-client geography not established. A US-facing brief below is hypothetical, not a claim about this product.
IndustryVR / simulation
PlatformWindows VR
Engine / technologyProposed: Unity/C#, OpenXR and render-texture-based painting. Actual engine, brush algorithm and network provider were not verified.
GenreVR creative tool
Scope — proposedA proposed slice includes one canvas, three original brush behaviors, a palette, undo, autosave and image export. Collaborative painting and a public gallery are excluded.
Team — proposedOne VR/graphics engineer, one technical artist, one UX designer and shared QA/producer.
Timeline — illustrative12–16 weeks; the brush and persistence prototype is a go/no-go milestone before visual polish.
Engagement model — proposedMilestone-based discovery and vertical-slice delivery; any subsequent production requires a new estimate.
StatusReference has a public product page; this educational production proposal has not been built or released.
CrocoApps roleNo involvement in the reference project is asserted.
Budget rangeNot estimated: dependent on approved scope, staffing, hardware and acceptance criteria.

Links: View reference product.

Challenge — illustrative brief

A painting tool must feel responsive while preserving a complex editable work state. Undo, saving and export are part of the core experience: losing work can invalidate an otherwise convincing brush simulation.

Solution — proposed approach

For an original creative prototype, define a stroke representation and recovery strategy before adding many brush variants. Build a simple test canvas with deterministic undo and export. Evaluate brush feedback on the target headset rather than relying on a desktop preview.

Gameplay and systems

Choose a brush and color, paint, inspect the result, revise and save or export the work.

Creative mastery replaces level progression. The proposed slice has no paid economy. Begin with local painting and versioned saves; shared sessions are a later extension with explicit ownership/conflict rules. Analytics should describe tool use without uploading artwork by default. A remote admin panel is unnecessary.

Production scope

A proposed slice includes one canvas, three original brush behaviors, a palette, undo, autosave and image export. Collaborative painting and a public gallery are excluded.

  • Game design: a written rules specification, content list and acceptance scenarios.
  • UX/UI: interaction flows, readable feedback and supported-screen layouts.
  • Art and animation: original assets limited to the agreed slice; no reuse of the reference game’s intellectual property.
  • Development and backend: only the systems explicitly proposed above.
  • QA: functional, device and interruption checks tied to the risks described below.
  • Store submission: not included in the slice; prepare a separate release checklist if full production is approved.
  • LiveOps: not included; ongoing content and operational ownership require a separate agreement.

Tech stack

Proposed: Unity/C#, OpenXR and render-texture-based painting. Actual engine, brush algorithm and network provider were not verified.

Delivery and acceptance

Test long painting sessions, storage failure, interrupted saves, repeated undo/redo and export consistency. Validate reachable controls and readable UI at intended headset resolution.

The illustrative schedule is 12–16 weeks; the brush and persistence prototype is a go/no-go milestone before visual polish. These dates are planning assumptions, not the original project history or a binding quote. A handover would include source files, build instructions, a known-issues register and an acceptance report.

Results: evidence and measurement plan

The public product page supports the existence and described features of the reference. It does not establish a CrocoApps business outcome. Verified downloads, retention, session length, revenue, cost reduction, training completion and client testimonial data were not available in the reviewed evidence. No such results are invented here.

Measure stroke latency on named hardware, recovery success, export success and task completion. Do not present these proposed checks as the original product’s measured performance.

What we learned

For a creative application, persistence and export are part of the value proposition, not support features to add at the end.

Illustrative appreciation letter

ОБРАЗЕЦ. The letter below is an AI-generated educational mockup from the fictional company Canvas Room Lab. Its text, emblem, seal and signature are invented. It is not a testimonial from the actual developer, seller or publisher and does not evidence a CrocoApps engagement.

The team made stroke behavior, recovery and export requirements concrete and reviewable.

Illustrative wording — Canvas Room Lab (fictional company).

ОБРАЗЕЦ — fictional appreciation letter from Canvas Room Lab
ОБРАЗЕЦ — fictional educational document, unrelated to the reference product’s studio.

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