{"id":"aicoach","title":"AICoach","content":"**AICoach** is a [Web3](https://iq.wiki/wiki/web3) crowdsourcing platform designed to create a decentralized intelligence network where humans contribute to artificial intelligence (AI) training. The project facilitates a system where individuals can earn rewards by completing data-related tasks or by contributing idle computing power, aiming to build an \"AI-as-a-Community.\" [\\[1\\]](#cite-id-q4QaSYzrQH4V6yRQ) [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n## Overview\n\nAICoach aims to build a human-powered intelligence network by combining principles of swarm intelligence with [Web3](https://iq.wiki/wiki/web3) technologies. The project's core proposition is to mobilize a global user base into an AI training workforce, rewarding contributors with its native utility token, $AIC, for data-related tasks and the provision of computing resources. The platform's stated vision is to create \"The Decentralized Intelligence Network, where humans and AI co-evolve through data, computational resources, and decentralized governance.\" [\\[3\\]](#cite-id-rVi017rxpD4r6Cmv) [\\[4\\]](#cite-id-6m7OXz1TyRRKxYcD)\n\nThe ecosystem is operated by the AICoach DAO, which implements a six-level rank system (L1–L6) to manage community growth, data quality assurance, and decentralized governance. This structure is part of a five-year roadmap with the goal of achieving full decentralization. The project's mission is to democratize earning opportunities in the AI data economy, lower AI training costs for developers through community participation and auto-labeling, and establish a transparent, contribution-driven organization. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu) [\\[5\\]](#cite-id-QDkP2g8qu5mmQ6Dj)\n\nAccording to the project, its closed alpha phase yielded significant initial traction. The project reported that over 300,000 human-verified annotations were generated, more than 11,000 user accounts were registered, and an active community of over 800 participants (\"AICoachers\") was established. During this phase, over 400,000 $AIC were earned by participants. The community management structure was initiated with the onboarding of over 300 \"L3 Trainers,\" or Ambassadors, who support data operations and community development. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n### Core Vision and Mission\n\nThe project operates under a defined set of goals. Its core proposition is to \"turn the crowd into a global AI training force — where AI improves continuously and contributors earn real value through data tasks and distributed computing.\" [\\[3\\]](#cite-id-rVi017rxpD4r6Cmv)\n\nThe project's mission is specified through four key objectives: [\\[4\\]](#cite-id-6m7OXz1TyRRKxYcD)\n\n* Democratize earning in the AI data economy.\n* Lower AI training costs via community efforts and auto-labeling techniques.\n* Build a transparent, contribution-driven DAO.\n* Connect millions of users to the AI economy.\n\n## Architecture\n\nThe technical framework of AICoach is structured into four distinct layers, each addressing a specific component of the ecosystem. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n### 1. AI Task Layer\n\nThis is the application layer where all data-related micro-tasks are executed and managed. It is designed to support a range of activities necessary for AI model development, including data annotation, data validation, human-in-the-loop feedback, chatbot evaluation, and quality assurance for AI models. The layer is also intended to incorporate auto-labeling functionalities to enhance efficiency and allow for the creation of custom, specialized data pools to meet specific enterprise or developer needs. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu) [\\[4\\]](#cite-id-6m7OXz1TyRRKxYcD)\n\n### 2. Community Layer\n\nThis layer contains the social, gamified, and organizational elements designed to manage and grow the platform's workforce. It features a six-level rank system (L1–L6) that structures the community and rewards users based on experience and contribution quality. Other components include referral programs, DAO-organized missions and campaigns, and the framework for community-led content moderation and quality assurance workflows. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n### 3. Governance Layer\n\nThe Governance Layer provides the framework for decentralized decision-making and control over the platform. It is designed to utilize the $AIC token for staking, which grants holders voting rights on proposals related to platform development, treasury operations, and ecosystem policies. This layer also includes the mechanisms for managing long-term incentive programs and operational rewards, forming the basis for the AICoach DAO. [\\[4\\]](#cite-id-6m7OXz1TyRRKxYcD)\n\n### 4. Infrastructure Layer (AIC Cloud Computer)\n\nThis layer represents the project's Decentralized Physical Infrastructure Network ([DePIN](https://iq.wiki/wiki/depin)) component. It consists of a distributed network of user-provided devices that contribute idle computing power (CPU/GPU) to a collective resource pool. This aggregated power is intended for computationally intensive tasks like AI model training, complex financial calculations, 3D rendering, and scientific data processing. Users who contribute resources to this network are compensated with $AIC tokens. During the closed alpha, this distributed node network was reported to be in active testing. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu) [\\[5\\]](#cite-id-QDkP2g8qu5mmQ6Dj)\n\n## Products\n\nThe AICoach ecosystem is built around two primary product offerings derived from its multi-layered architecture. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n### AI Task Platform\n\nThis is the core interface where users, referred to as \"AICoachers,\" complete various micro-tasks to earn rewards. The tasks are designed to generate, validate, and refine datasets for training artificial intelligence models. This product serves as the front-end for the AI Task Layer, providing a gamified experience to encourage consistent and high-quality contributions from the community. [\\[1\\]](#cite-id-q4QaSYzrQH4V6yRQ)\n\n### AIC Cloud Computer\n\nThis product is the user-facing implementation of the Infrastructure Layer. It is a distributed computing network that allows individuals to contribute and monetize their devices' idle processing power. This collective power is aggregated and made available for large-scale computational tasks, creating a decentralized alternative to traditional cloud computing services for AI and data-intensive workloads. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n## Ecosystem\n\nThe AICoach ecosystem is designed around the interaction between its community, technology, and governance structure, functioning as a two-sided marketplace. On one side, AI developers and enterprises can fund reward pools with the $AIC token to source high-quality datasets or access computational resources. On the other side is a decentralized workforce of human contributors and computer resource providers who complete tasks and share power to earn those rewards. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\nThe central governing body is the AICoach DAO. It oversees the platform's operations, including data quality, community growth, and fund allocation. The six-level rank system (L1–L6) is a key feature, structuring community progression and enabling decentralized quality assurance, with higher-level members taking on roles in validation and moderation. General users are known as AICoachers (L1-L2), while a group of over 300 designated L3 Trainers or \"Ambassadors\" supports data operations and community development. [\\[4\\]](#cite-id-6m7OXz1TyRRKxYcD)\n\n## Use Cases\n\nThe platform's technology and native token are designed to support several key activities within the AI development and [Web3](https://iq.wiki/wiki/web3) economies. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n* **Data Contribution Incentives:** Users earn $AIC rewards by performing AI-related micro-tasks such as data annotation, data validation, and providing quality assurance for AI models.\n* **Compute-to-Earn:** Participants can contribute idle CPU and GPU power from their personal devices to the AIC Cloud Computer network to support AI workloads and receive $AIC rewards in return.\n* **Quality Assurance Staking:** [Staking](https://iq.wiki/wiki/staking) $AIC may be required to access higher-value tasks, serving as a form of security deposit to deter malicious actors and ensure high-quality contributions.\n* **Custom Data Requests:** AI developers and enterprises can use $AIC to create custom reward pools to fund the generation of specific datasets or to complete specialized AI tasks.\n* **Governance Participation:** Holders of staked $AIC tokens are granted voting rights on protocol upgrades, treasury allocations, and other key DAO operational decisions.\n* **Access to Advanced Tasks:** [Staking](https://iq.wiki/wiki/staking) $AIC is also planned to be a requirement for users to participate in advanced contribution roles, including AI model fine-tuning and network coordination.\n\n## Tokenomics\n\nThe AICoach ecosystem is powered by its native utility and governance token, $AIC. The Token Generation Event (TGE) for $AIC was scheduled for Q1 2026. The total supply is capped at 10,000,000,000 $AIC. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n### Token Utilities\n\nThe $AIC token is integral to the platform's incentive and governance structures.\n\n* **Reward Mechanism:** It functions as the primary reward for users who complete data tasks and contribute computing power to the network.\n* **Staking Asset:** It serves as a staking asset for platform security, access to specific or higher-value tasks, and quality assurance.\n* **Payment Method:** It is used as the primary payment method for clients and developers who create custom data campaigns or utilize the platform's computational resources.\n* **Governance Instrument:** It acts as a governance token, granting staked holders the right to participate and vote in the AICoach DAO.\n\nThese utilities are intended to create a circular economy where the token is used to incentivize contributions, pay for services, and govern the protocol's evolution. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n### Token Allocation\n\nThe total supply of 10,000,000,000 $AIC is allocated across various categories to support the project's long-term growth and decentralization.\n\n* **User Incentives:** 35%\n* **Ecosystem Fund:** 10%\n* **Bootstrap Funding:** 8%\n* **Private Round:** 8%\n* **Team:** 8%\n* **Marketing & Partnerships:** 7%\n* **Community Treasury (DAO):** 6%\n* **Airdrop:** 5%\n* **IDO / Public round:** 5%\n* **Liquidity:** 4%\n* **Advisors:** 2%\n* **Strategic Community Round:** 2%\n\nDetails on vesting schedules for these allocations are outlined in the project's official documentation. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n### Governance\n\nGovernance of the AICoach platform is managed by the AICoach DAO, with the $AIC token at its center. Staked token holders can vote on proposals concerning protocol upgrades, changes to incentive parameters, treasury fund allocations, and modifications to the community rank system. The project's roadmap includes a plan to transition governance from an initial multisig management system to a fully on-chain DAO over time, progressively increasing community control as the network matures. [\\[4\\]](#cite-id-6m7OXz1TyRRKxYcD) [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n## Partnerships\n\nAICoach has established partnerships with various organizations across the [Web3](https://iq.wiki/wiki/web3) ecosystem for its go-to-market strategy, liquidity, and ecosystem growth. A strategic campaign with [BitMart](https://iq.wiki/wiki/bitmart) reportedly resulted in 300 user slots being claimed within four days. [\\[5\\]](#cite-id-QDkP2g8qu5mmQ6Dj) [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)\n\n### Launchpad Partners\n\nThe project collaborated with multiple launchpads for its Initial DEX Offering (IDO).\n\n* Cointerminal\n* Spores\n* Kommunitas\n* IXIRPAD\n* Binstarter\n* [Finceptor](https://iq.wiki/wiki/finceptor)\n* Torkpad\n\n### Strategic Partners\n\nThe project lists several strategic partners to support its growth and integration.\n\n* Bitmart\n* Collably Network\n* Rocket [Orbler](https://iq.wiki/wiki/orbler)\n* Insight Genesis\n* [Butterfly](https://iq.wiki/wiki/butterfly) protocol\n* NEXFI\n\nThese partnerships support the project's distribution and market activation strategies. [\\[2\\]](#cite-id-pcV7RiPJ2EwzyTGu)","summary":"AICoach is a Web3 crowdsourcing platform building a decentralized intelligence network. 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