# Roadmap

Our roadmap outlines key milestones as we continue to build an immersive, player-driven ecosystem that bridges real-world and metaverse escape rooms.

**Q2 2025: $ERM Launch Preparation & Public Sale**

* Conduct public sale of $ERM on Virtuals Protocol and Genesis Launchpad.
* Airdrop $VIRTUALS to The Wonderist Avatar NFT holders to boost secondary market activity.
* Begin outreach to global escape room partners for pilot integrations.

**Q3 2025: Platform Expansion & AI Agent Deployment**

* Launch ERM DApp MVP featuring booking integration, XP tracking, and on-chain profiles.
* Launch AI Agents to score Player Performance Matrix based on behavioural, emotional and decision-making data.
* Enable O2O integration: link escape room bookings, XP, and NFT progress across physical and digital touch-points.
* Finalize token listing on centralized exchange (CEX) post-sale.

**Q4 2025: Creator Tools & Community Growth**

* Introduce Marketplace MVP for AIGC & UGC assets (script, maps, NPCs, puzzles).
* Launch Creator Studio for custom escape room publishing with AIGC tools.
* Reward top creators and players with $ERM and XP.
* Host cross-platform campaigns with The Wonder World IP.
* Activate governance staking for early holders.

**Q1 2026: Ecosystem Flywheel & AI-driven Scaling**

* Expand AI Agent features to adapt NPCs and puzzles in real time.
* Onboard partner escape rooms globally.
* Integrate third-party game data into Player Performance Matrix.
* Launch Season 1 of Escape Room 3.0 IP titles.
* Expand marketing with localized campaigns and influencer activations.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://erm-labs.gitbook.io/whitepaper/welcome-to-erm-labs-and-entivo/project-overview/roadmap.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
