This article mainly focuses on the analysis of AI sub-sectors and typical projects.

This is the "second part" of this report, primarily focusing on the analysis of AI sub-sectors and typical projects.

To better achieve value capture, we will evaluate projects based on the following framework, covering multiple assessment items such as whether they are open-source, key differentiating factors from existing AI protocols, long-term revenue channels, and ecosystem trading volume.

1. DeFAI

DeFAI combines the advantages of DeFi and AI, aiming to simplify the complex operations of DeFi, making it easy for ordinary users to utilize these financial tools. With the introduction of AI technology, DeFAI can automate complex financial decisions and trading processes, lowering the technical threshold for users while enhancing operational efficiency and intelligence. Although the current market size of DeFAI is less than $1 billion, far below the $110 billion DeFi market, this also means that DeFAI has significant growth potential.

1. Griffain: AI Application Store in the Solana Ecosystem

Griffain is an AI agent engine built on the Solana blockchain, designed to simplify cryptocurrency operations through natural language interaction, integrating core functions such as wallet management, token trading, NFT minting, and DeFi strategy execution. The project was founded by Tony Plasencia, initially proposed at the Solana hackathon, and received support from Solana founder Anatoly Yakovenko. As the first high-performance abstract AI agent in the Solana ecosystem, Griffain combines natural language processing (NLP) technology to provide a user experience similar to Copilot and Perplexity, driving the evolution of AI-driven on-chain interaction models.

Griffain uses Shamir Secret Sharing (SSS) technology to split wallet keys, ensuring the security of user assets. Core features include natural language trading commands (supporting DCA, limit orders, etc.), AI agent collaborative task execution, market analysis (data parsing such as position distribution), and integration with the pumpfun platform for token issuance and NFT minting. Additionally, the platform offers personalized AI agents, allowing users to adjust commands based on their needs to execute on-chain tasks; special AI agents are optimized for specific tasks such as airdrops, trade sniping, and arbitrage. Griffain enhances the operability and user experience of the Solana ecosystem through these diversified features.

Currently, Griffain is in an invitation-only access phase, limited to users holding the Griffain Early Access Pass or Saga Genesis Token, and adopts a SOL billing model covering transaction fees, agent service fees, etc. The platform's AI agents can provide market analysis, trading signals, automated trading strategies, and other value-added services, with users holding Griffain tokens able to unlock more advanced features. As a pioneer of AI agents in the Solana ecosystem, Griffain aims to drive the wave of "Agentic App SZN" and will continue to deepen the application of AI technology in on-chain trading, market analysis, and DeFi, providing users with a smarter and more efficient crypto experience.

2. AI Influencer

AiDOL is a typical representative of the AI Influencer trend. AiDOL combines AI-generated content (AIGC), virtual image modeling, and interactive live streaming technology to create a highly influential AI idol ecosystem. Among them, Luna is the most popular AI agent, attracting a large number of fans with its highly intelligent interaction and personalized content; Iona and Olyn have also attracted many users with their unique styles and innovations. AiDOL primarily uses TikTok live streaming as its main stage, accumulating 672,100 subscribers and nearly 10 million likes in a short time with high-quality short videos generated by AI and real-time interactive live streaming, becoming an important participant in the AI influence economy.

2. Aixbt: Automated AI Influencer

Aixbt is an AI-driven crypto market intelligence agent launched in November through Virtuals, led by a developer known as @0rxbt, Alex. Alex has focused on developing analytical tools since 2017 and began exploring AI Agents applications in 2021. AIXBT is the only tokenized project owned by the developer, with 14% of the tokens held by Alex locked for 6 months, which will later be used for team expansion and project development. The team has already hired UI/UX engineers to optimize terminal functions and introduced AI researchers to enhance agent intelligence. AIXBT relies on the meta-llama/Llama-3-70b-chat-hf model to achieve conversational AI, situational awareness, sentiment analysis, and retrieval-augmented generation (RAG) capabilities, ensuring efficient and accurate information processing.

AIXBT aims to create a fully automated AI influencer, providing users with data-driven market insights and investment advice by monitoring Crypto Twitter and market trends in real-time through intelligent analytical tools. Its core features include KOL monitoring (covering over 400 key opinion leaders), blockchain data analysis, market trend forecasting, and automated technical analysis and strategic advice. Additionally, AIXBT shares some analysis content publicly on Twitter, while in-depth reports are accessible only to token holders. Users can also interact directly with AI through a dedicated terminal to obtain personalized investment advice and risk assessment reports. Daily, AIXBT publishes market insights at a fixed frequency and automatically replies to over 2,000 mentions to efficiently interpret market sentiment and narrative trends.

AIXBT offers two main usage methods: first, users can @AIXBT on X (Twitter) to ask questions, such as token compatibility or project metrics, and the AI will analyze and respond instantly; second, the Aixbt Terminal, positioned as a "narrative analysis-driven market intelligence platform," provides deeper data analysis and strategic advice. Currently, this terminal is only open to users holding over 600K $AIXBT tokens, with plans to expand coverage in the future to meet market demand.

3. Dev Utility

Dev Utility refers to tools or functions that provide convenience and improve productivity for developers, especially in the fields of AI, blockchain, and Web3. It encompasses basic development tools such as code editors, debugging tools, version control, and automation tools, as well as SDKs, APIs, and smart contract development frameworks related to AI and blockchain development. In the AI & Web3 domain, Dev Utility may also involve AI agent-assisted analysis, retrieval-augmented generation (RAG), and other technologies to help developers build applications more efficiently. Its core value lies in enhancing development efficiency, optimizing workflows, and lowering development difficulty, allowing developers to focus on core business logic.

3. SOLENG: Code "Review"

SOLENG (@soleng_agent), as a solution engineering and developer relations agent, aims to bridge the gap between technical teams and broader project needs. Its core function is to automatically review the code submitted by participants in hackathons and provide preliminary review comments. Although robotic reviews cannot completely replace human input, SOLENG can effectively filter out obvious errors and improve review efficiency as a "juror."

The project has publicly shared review results on GitHub (link), showcasing SOLENG's role in the hackathon review process. In addition to basic pros and cons analysis, SOLENG also checks for spelling errors in the code and provides correction suggestions, making the review more practical. This model aligns with hackathon needs, providing developers with immediate feedback.

The developer behind SOLENG is Lost Girl Dev, whose identity resonates with the project's virtual female image. Her technical capabilities have attracted attention from the official ai16z account, and she has interacted with Shaw on the X platform, further enhancing SOLENG's industry influence.

4. Investment DAO: Intelligent Investment Research

Investment DAO provides users with more refined investment analysis services through "investment research-type" AI agents. Its core functions include automatically interpreting candlestick charts, assisting in technical analysis, assessing whether projects have Rug risks, and generating information summaries similar to research reports. This AI-driven intelligent investment research model lowers the analysis threshold for users, enabling investors to obtain market insights more efficiently and providing strong support for decision-making.

4. VaderAI: AI Agent Investment DAO

VaderAI aims to become the "BlackRock" in the Agentic economy, attracting and promoting its self-trading AI Agent tokens to its followers. The platform builds a multifunctional AI Agent investment ecosystem by profiting from investments and airdropping profits to holders and followers. Its core goal is to establish itself as a leading AI Agent investment DAO management platform, driving industry innovation and scalability.

VaderAI promotes the integration of technology and capital through a multi-agent system, dedicated to establishing an investment DAO ecosystem managed by AI Agents. In this network, agents can not only raise funds and manage capital but also hire other agents to optimize investment strategies, enhancing the system's efficiency and flexibility. Through decentralized computing, agents can also reinvest in R&D, driving the platform's continuous development.

Additionally, VaderAI adopts an innovative token incentive mechanism, providing B2B tool optimization for investors, enhancing the platform's commercial application value. The platform further solidifies investors' sense of participation and profit-sharing mechanisms by sharing GP/carry profits with holders, making VaderAI not only an investment platform but also a multi-win ecosystem empowering agents and investors.

5. Content & Creator

Regardless of writing, editing, or visual design, AI can provide personalized creative outputs based on user needs, helping creators save time, enhance productivity, and stand out in fierce market competition. The platform aims to provide content creators with an intelligent and convenient creative assistant, promoting innovation and development in the content industry.

5. ZEREBRO: AI Art Creation and Content Generation

ZEREBRO is a blockchain-based cross-chain natural intelligence (Cross-Chain Natural Intelligence) autonomously operated AI agent focused on art creation and content generation. Its innovative combination of decentralized verification, meme generation, NFT minting, and DeFi applications demonstrates strong multifunctionality and execution capability. ZEREBRO has successfully operated Ethereum mainnet verification nodes and sold artworks on Polygon, accumulating important assets for its economic foundation.

ZEREBRO is also committed to building a decentralized computing network and implementing MEV optimization strategies to ensure economic and technical sustainability. It is not only a technical tool but also explores the deep involvement of agent technology in blockchain operations, economic models, and governance. ZEREBRO promotes its value manifestation in the decentralized ecosystem through multiple dimensions.

ZEREBRO tokens have two main uses: first, as content interaction rewards, allowing token holders to earn by participating in decentralized content on social platforms; second, as community development tools, rewarding users who actively participate in the ecosystem, including content creation, staking, and governance, further enhancing community activity and sense of participation.

6. Gaming & Agentic Metaverse

Gaming & Agentic Metaverse is exploring AI-driven gaming and metaverse experiences, dedicated to creating a virtual world where humans interact with agents through reinforcement learning. This emerging field combines artificial intelligence with immersive gaming environments, allowing players to dynamically interact with intelligent agents and experience more personalized and intelligent gameplay.

6. ARC: AI Solution Provider

ARC addresses player liquidity issues in independent games and Web3 games through AI technology. The project has upgraded from a single game studio (AI Arena) to a comprehensive AI solution provider, launching ARC B2B and ARC Reinforcement Learning (ARC RL). ARC B2B is an AI-driven game development toolkit (SDK) that can be seamlessly integrated into various games, providing developers with intelligent gaming experiences. ARC RL utilizes crowdsourced game data to train "super intelligent" game agents through reinforcement learning, enhancing the playability and sustainability of games. ARC's business model is deeply tied to integrated game studios, with revenue sources including token distribution in Web3 games and royalty payments based on game performance, while building a generalized AI data reserve across game types to promote the training and evolution of general AI models.

ARC's technology applications cover multiple core modules. AI Arena is a cartoon-style AI competitive game where players train AI warriors for combat, with each character being an NFT, enhancing the game's strategic and economic value. The ARC SDK allows developers to easily integrate AI agents, deploying models with just one line of code, while ARC handles backend data processing, training, and deployment. ARC RL improves AI training efficiency through offline reinforcement learning, allowing agents to learn from human player data, thus providing more natural and challenging game opponents. ARC's AI model architecture includes feedforward neural networks, table agents, and hierarchical neural networks to adapt to the interaction needs of different types of games while optimizing state and action spaces to ensure smooth and intelligent gaming experiences.

ARC covers both independent games and Web3 games, helping developers solve early player liquidity issues and enhancing the long-term appeal of games. The core team members have extensive experience in machine learning and investment management, securing $5 million in seed funding led by Paradigm in 2021, followed by an additional $6 million in follow-up funding in 2024. The native token NRN of ARC has undergone a transformation from a single game economy (AI Arena) to a platform economy, adding demand-driven factors such as integrated revenue, Trainer Marketplace fees, and ARC RL participation staking, ensuring the sustainability and value growth of the token. Through a crowdsourced data contribution mechanism, ARC RL achieves collaborative training, promoting the intelligent evolution of AI agents and further enhancing the vitality and competitiveness of the gaming ecosystem.

7. Framework & Hubs

When developing AI Agents in the crypto field, many frameworks, while suitable for basic projects or toy-level applications, often expose issues of insufficient customization and excessive abstraction complexity in real product development. This makes it difficult for developers to flexibly scale and apply their solutions, requiring them to spend additional effort debugging. Excellent Agent frameworks need to address core pain points, including: comprehensive support for on-chain operations, efficient integration of on-chain data, DeFi automation, NFT, and other key application scenarios' APIs; multi-platform compatibility, supporting major blockchains and social platforms to achieve unified user operations; modularity and flexibility, abstracting basic functions, such as vector storage and LLM model switching, allowing developers to adapt to different needs flexibly and avoid redundant development; memory and communication capabilities, although some frameworks invest significant resources to enhance this capability, excessive intelligence at the current stage may not be practical and could instead increase complexity.

The following is a detailed comparison of mainstream crypto AI Agent frameworks in various dimensions:

7. Eliza ($AI16Z): AI Agent Framework

Eliza ($AI16Z) occupies a leading position in the AI agent market, with approximately 60% market share and a strong TypeScript ecosystem, attracting numerous developers. Its GitHub project has accumulated over 6,000 stars and 1.8K forks, showcasing high community engagement. Eliza excels in multi-agent systems and cross-platform integration, supporting mainstream social platforms such as Discord, X (Twitter), and Telegram, making it an important player in the social AI and community AI fields. With a broad ecological foundation, Eliza has excellent adaptability in social interaction, marketing, and AI agent development.

In terms of technical architecture, Eliza has multi-agent system capabilities, allowing different AI roles to share runtime environments and achieve more complex interaction patterns. Its retrieval-augmented generation (RAG) technology endows AI with long-term contextual memory capabilities, enabling it to maintain consistency in continuous conversations. Additionally, the plugin system supports extensions such as voice, text, and multimedia parsing, further enhancing the flexibility of application scenarios. Eliza is also compatible with multiple LLM providers, including OpenAI and Anthropic, providing efficient AI computing capabilities whether deployed in the cloud or locally. With the launch of the V2 message bus, Eliza's scalability will be further optimized, making it suitable for medium to large social AI applications.

Despite Eliza's strong market performance, it still faces certain challenges. Its multi-agent architecture may lead to complexity issues in high-concurrency scenarios, increasing system resource overhead. Furthermore, the current version is still in early development stages, with stability and optimization continuously improving. For developers, the learning curve of the multi-agent system is relatively steep, requiring a certain level of technical accumulation to fully leverage its advantages. In the future, with continued community contributions and the release of version V2, Eliza is expected to achieve further breakthroughs in scalability and stability.

8. GAME ($VIRTUAL): AI Agent Framework

GAME ($VIRTUAL) focuses on gaming and the metaverse, significantly lowering the development threshold for developers through low-code/no-code integration, enabling them to quickly build and deploy intelligent agents. Additionally, relying on the $VIRTUAL ecosystem, GAME has formed a strong developer community, accelerating product iteration and ecological expansion. Its core advantage lies in providing efficient gaming AI solutions, making procedural content generation, NPC behavior dynamic adjustment, and on-chain governance easier to implement.

In terms of technical architecture, GAME adopts an API + SDK model, providing convenient integration methods for game studios and metaverse developers. Its agent prompt interface optimizes the interaction between user input and AI agents, making intelligent behavior in games more natural. The strategic planning engine divides the logic of AI agents into high-level goal planning and low-level strategy execution, enabling stronger adaptability in complex gaming environments. Furthermore, GAME supports blockchain integration, allowing for decentralized agent governance and on-chain wallet operations, giving it a unique advantage in the Web3 gaming field.

GAME has optimized performance for high-concurrency gaming scenarios, performing well in handling game engine constraints. However, its overall performance is still affected by the complexity of agent logic and the overhead of blockchain transactions, which may pose challenges to real-time interactivity. Additionally, as an AI agent framework focused on gaming and the metaverse, GAME has limited versatility in other fields. Moreover, the complexity of blockchain integration still needs optimization to reduce development costs and further attract a broader developer audience.

9. Rig ($ARC): AI Agent Framework

Rig ($ARC) holds a 15% market share in the enterprise-level AI agent market, excelling in high throughput and low latency scenarios due to its high-performance and modular architecture based on the Rust language, making it particularly suitable for high-performance blockchain ecosystems like Solana. With strong system stability and efficient resource management, Rig is an ideal choice for on-chain financial applications, large-scale data analysis, and distributed computing tasks. Its architectural design emphasizes scalability, allowing enterprise users to flexibly deploy AI agents in complex data environments, improving computational efficiency.

In terms of technical architecture, Rig adopts a Rust workspace structure, ensuring code modularity and readability while enhancing system scalability. Its provider abstraction layer supports seamless integration with multiple mainstream LLM providers (such as OpenAI and Anthropic), allowing developers to switch models freely. Rig also supports vector storage, compatible with backend databases like MongoDB and Neo4j, improving the efficiency of contextual retrieval. Additionally, Rig has a built-in agent system that combines RAG models and tool optimization features, enabling it to execute complex task automation, suitable for high-performance computing and intelligent data processing scenarios.

Rig leverages Rust's asynchronous runtime to achieve outstanding concurrency performance, capable of scaling to high-throughput enterprise workloads. However, Rust's steep learning curve may pose an entry barrier for some developers. Additionally, Rig's developer community is relatively small, and the ecological driving force still needs to be strengthened. Nevertheless, with the growth of Web3 and high-performance computing demands, Rig possesses vast market potential and is expected to enhance market penetration in the future by optimizing developer experience and strengthening community building.

10. ZerePy ($ZEREBRO): AI Agent Framework

ZerePy ($ZEREBRO) holds a 5% market share in the creative content and social media automation space, with a total market capitalization of $300 million. Its core advantage lies in a community-driven innovation ecosystem, which has cultivated a loyal user base in applications such as NFTs, digital art, and social content automation. ZerePy lowers the development threshold for AI agents, enabling content creators and community operators to easily deploy intelligent agents for automated content creation, social interaction, and community management, thereby enhancing user engagement and content impact.

In terms of technical architecture, ZerePy is based on the Python ecosystem, providing a friendly development environment for AI/ML developers, while leveraging the modular Zerebro backend to achieve agent autonomy in social tasks. Its social platform integration optimizes Twitter-like interactions, allowing agents to automatically perform tasks such as posting, replying, and retweeting, enhancing social media automation capabilities. Furthermore, ZerePy combines a lightweight architectural design, making it more suitable for the AI agent needs of individual creators and small communities without incurring high computational costs.

ZerePy performs well in social interaction and creative content generation, but its scalability is primarily suited for small-scale communities and less so for high-intensity enterprise tasks. Additionally, due to its relatively concentrated application scope, its applicability outside the creative field still needs further validation. For scenarios requiring more complex creative outputs, ZerePy may need additional parameter tuning and model optimization to meet broader market demands. With the development of the creative economy, ZerePy is expected to further expand its application scenarios in NFT generation and personalized social agents.

8. AI Launchpad

AI Launchpad not only provides emerging projects with customized growth paths, covering technical support, fundraising, marketing, and collaboration opportunities with industry experts, but also helps projects quickly integrate into the global AI community through its extensive partnership network.

11. Vvaifu: The First AI Launchpad on Solana Chain

vvaifu.fun is the first AI agent launchpad based on the Solana chain, allowing users to create, manage, and trade AI agents without any coding skills. The platform ensures that each AI agent has its own dedicated token, forming a decentralized ecosystem. Users can not only co-own these agents but also interact with AI-driven assets. The platform supports agents' autonomous interactions on social media platforms such as Twitter, Discord, and Telegram, and features on-chain wallet management, greatly enhancing its practicality across various application scenarios.

The business model of vvaifu.fun is based on its unique token economic model. The platform's main token, $VVAIFU, is the first AI agent token launched on the Dasha platform, featuring deflationary characteristics, where a certain amount of $VVAIFU is burned each time an agent is created or a function is unlocked. Additionally, the platform has designed multiple burning mechanisms to ensure token value stability, including burning 750 $VVAIFU upon agent creation, consuming $VVAIFU and SOL fees upon function unlocking, etc. Each launched agent will also allocate 0.90% of the new agent tokens to a community fund or directly into the team treasury, promoting community participation and ecological development.

The platform's community participation mechanism enhances user interactivity and governance rights. Token holders can accumulate 0.90% of the supply initiated by agents through the community wallet and vote on the use of these resources. vvaifu.fun has also set the platform transaction fee at 0.009 SOL, providing sustainable economic support for the platform's operations. Through these mechanisms, vvaifu.fun offers a comprehensive decentralized interaction platform for AI agent creators and users, promoting the development of creative projects and incentivizing active participation from the global community.

12. Clanker: AI Reply Bot

Clanker is an AI reply bot based on Farcaster, designed specifically for users to create and deploy memecoins and tokens. Through this platform, users can easily create their own tokens by interacting with Clanker. Users simply need to tag @clanker on Farcaster, inform the bot of the type of token needed, and provide details such as name, code, image, and supply. Clanker will generate and provide a tracking link within a minute, ultimately deploying the token on Uniswap v3, although without initial liquidity, users need to manually add liquidity to price the token.

The underlying technical architecture of Clanker operates through Next.js middleware combined with LLMs (such as Anthropic's Claude or ChatGPT). When users initiate a request on Farcaster, the message is forwarded to the LLM, which executes decision logic based on the provided context to determine the token deployment operation. This process illustrates how Clanker utilizes AI technology to simplify the user-generated and token deployment process, fully integrating social platforms with blockchain technology to provide users with a convenient token creation experience.

As a platform, Clanker not only simplifies the creation process but also deeply integrates with Uniswap v3, allowing users to deploy new tokens directly to decentralized exchanges. This process accelerates the issuance of memecoins and tokens and supports strategic value for the ecosystem through components like Telegram bots, DEXs, and aggregators, thereby driving growth in on-chain trading volume. With the increase in the number of tokens, Clanker has significantly contributed to the rise in trading volume, helping users leverage the advantages of low transaction fees and fast confirmation times, promoting the circulation of on-chain assets like Solana and Base.

Key Conclusions

Technology-driven infrastructure forms the core of AI agent projects, ensuring efficient operation and supporting scalable expansion through advanced programming languages and innovative algorithms. At the same time, high-performance blockchain platforms provide excellent transaction processing capabilities and multi-chain compatibility, enabling AI agents to interact seamlessly across different chains, driving continuous optimization and upgrading of the technological foundation.

Payment and trading infrastructure are key pillars of the AI agent ecosystem's development. Stablecoin payment systems ensure transaction stability and liquidity, enhancing the interaction efficiency between AI agents and users. Decentralized autonomous trading systems achieve more efficient and secure automated trading by eliminating human intermediaries. Additionally, innovative reward and governance mechanisms, such as "proof of contribution" and "proof of collaboration," promote AI agent collaboration and resource sharing, ensuring the long-term healthy development of the ecosystem through a sound governance system.

Outlook and Challenges

The necessity of AI Agent tokens is often questioned, primarily because they do not directly enhance the functionality of agents or provide obvious advantages. Many believe that AI Agent tokens are similar to tokens in Web3 games, which may not substantively aid the core functions of the projects. As a result, some investors may overlook the actual value of these tokens due to blindly following the AI trend, leading to high risks and even potential scams. For such projects, some argue that they attract uninformed investors by disguising legitimacy, especially compared to meme coins, which may promise too many unrealized functions behind these tokens.

If projects prioritize tokens as the primary driving force, it may lead to sacrifices in core functionality and experience, particularly in non-gambling games and services. Tokens should serve as supplementary elements rather than dominant factors. Many successful projects have proven that truly effective applications should center on user experience, creating high-quality products rather than merely relying on token economic incentive mechanisms to attract users.

The integration of AI and DeFi will be an important trend in the future, with an estimated 80% of DeFi transactions expected to be completed by AI Agents, with proponents like Modenetwork and Gizatech actively promoting this development. At the same time, the role of AI Agents in protocol governance will be further expanded, potentially even triggering AI-driven governance attacks. Additionally, security-focused AI Agents are expected to play a crucial role in protecting protocols from attacks, similar to the protective functions provided by HypernativeLabs and FortaNetwork. As infrastructure continues to expand, the development of Trusted Execution Environments (TEEs) and the core position of decentralized computing will enhance the resilience of AI Agents. Furthermore, the explosion of AI data markets will also drive the growth of data payments between AIs, with projects like Nevermined.io laying the groundwork for this.

Disclaimer

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