# ROME: Bounty & Rewards Platform When we decided to build an NFT project we looked for a tool to keep our community engaged and rewarded. A tool that we could use for gamification and incentives and didn't find anything we liked, so we built our own solution So what is Rome? In simple terms, it's an XP Based Bounty platform where communities can send their members on quests/missions for XP. They can then use that XP in the ROME store to redeem for NFTs, WL, and IRL Items, members can also participate in raffles and buy mystery boxes. We opened our Discord the last week of November 2021, without intentions of monetizing the ROME platform. But members of different communities started to ask if they could use the software for their own communities. We then started to research the competition Existing Competition and Pricing: * Communi3 (Charging $5k per instance) Too expensive and the solution is too simple * Crew3 (Free Access to their base platform, doesn't have a store or much gamification as communities like) How much does the ROME platform costs? It costs USD $1000/m for the basic version which includes: * Unique Rome Instance with Community Color Preferences * Hosted in a 2TB, 4 Ram, 2 VCPU server * XP-based platform + Store * Account Manager * Discord Integration * 24-26 hour SLA * Admin Panel There are add-ons you can choose for your Instance like: * Secondary XP token ($99/m) * XP Based Raffles ($199/m) * Mystery Boxes ($99/m) * Analytics ($99/m) * API integration with other apps ($99-199/m) * Leaderboard ($49/m) * SPL Integration ($199/m) --- # 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://jedidiah-eeics-organization.gitbook.io/elite-emperors/fundamentals/rome-bounty-and-rewards-platform.md?ask= ``` 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.