OKX Ventures Research Report: Deconstructing 10+ Projects to Help You Understand the AI Agent Landscape (Part 2)

Source: OKX

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

For better value capture, we will evaluate projects based on the following framework, covering multiple assessment criteria such as open-source nature, key differentiation factors from existing AI protocols, long-term revenue streams, and ecosystem's proxy transaction volume.

Part One: DeFAI

DeFAI combines the strengths of DeFi and AI, aiming to simplify the complex operations of DeFi so that ordinary users can easily use these financial tools. Through the introduction of AI technology, DeFAI can automate complex financial decisions and transaction processes, reduce user's technical barriers, and enhance operational efficiency and intelligence level. 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: Solana's AI App Store

Griffain is an AI agent engine built on the Solana blockchain, aiming 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 a Solana hackathon, and has received support from Solana's 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 interactions.

Griffain uses Shamir Secret Sharing (SSS) technology to split wallet keys, ensuring user asset security. Core features include natural language trading commands (supporting DCA, limit orders, etc.), AI agent collaborative task execution, market analysis (position distribution data analysis), as well as integration with the pumpfun platform for token issuance and NFT minting. Additionally, the platform provides personalized AI agents (Personal Agents) that allow users to adjust commands according to their needs to execute on-chain tasks; special AI agents (Special Agents) are optimized for specific tasks such as airdrops, front-running, arbitrage, etc. Through these diverse functions, Griffain enhances the operability and user experience of the Solana ecosystem.

Currently, Griffain is in the invitation-only access stage, limited to users holding the Griffain Early Access Pass or Saga Genesis Token, and follows an SOL billing model covering transaction fees, agent service fees, etc. The platform's AI agent can provide value-added services such as market analysis, trade signals, and automated trading strategies. Users holding the Griffain token can unlock more advanced features. As a pioneer in Solana's ecosystem AI agent, Griffain aims to drive the "Agentic App SZN" wave, and will continue to deepen the application of AI technology in on-chain trading, market analysis, and DeFi, providing users with a more intelligent and 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 a large number of users with their unique styles and innovation. AiDOL's main stage is TikTok Live, relying on high-quality AI-generated short videos and real-time interactive live streaming, accumulating 672,100 subscribers in a short time, receiving nearly 10 million likes, and becoming a key participant in the AI influence economy.

2. Aixbt: Automated AI Influencer

Aixbt is an AI-driven crypto market intelligence body, launched in November through Virtuals and led by the pseudonymous developer Alex (@0rxbt). Alex has been focusing on analytical tool development since 2017 and started exploring AI Agents applications in 2021. As the only tokenized project owned by the developer, Alex holds 14% of the tokens and locks them for 6 months, which will be used for team expansion and project development in the future. The team has already hired a UI/UX engineer to optimize terminal functionality and introduced an AI researcher to enhance agent intelligence. AIXBT leverages the meta-llama/Llama-3-70b-chat-hf model to achieve conversational AI, context awareness, sentiment analysis, and retrieval-augmented generation (RAG) capabilities, ensuring efficient and accurate information processing.

AIXBT aims to build a fully automated AI influencer that leverages intelligent analysis tools to monitor Crypto Twitter and market trends in real time, providing users with data-driven market insights and investment advice. Its core features include KOL monitoring (covering 400+ key opinion leaders), blockchain data analysis, market trend prediction, and automated technical analysis with strategic recommendations. Additionally, AIXBT publicly shares some analysis content on Twitter, while in-depth reports are only accessible to holders. Users can also interact directly with the AI through a dedicated terminal to receive personalized investment advice and risk assessment reports. Every day, AIXBT releases 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 modes: users can ask questions to @AIXBT on Twitter to inquire about token compatibility or project metrics, and the AI will promptly analyze and provide feedback; alternatively, the Aixbt Terminal is positioned as a "narrative analysis-driven market intelligence platform," offering deeper data analysis and strategic advice. Currently, this terminal is only open to users holding over 600K $AIXBT tokens, but will expand its coverage in the future to meet market demand.

Three, Dev Utility

Dev Utility refers to tools or features that provide convenience and enhance productivity for developers, especially in the AI, blockchain, and Web3 fields. 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 domains, Dev Utility may also involve technologies like AI agent-assisted analysis and retrieval-augmented generation (RAG) to help developers build applications more efficiently. Its core value lies in improving development efficiency, optimizing workflows, and reducing development complexity, enabling 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 the tech team and broader project needs. Its core function is to automatically review code submitted by hackathon projects and provide preliminary review feedback. While automated code review cannot fully replace human review, SOLENG serves as a "juror" to effectively filter out obvious errors and enhance the review efficiency.

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

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

Four, Investment DAO: Smart Invest-research

Investment DAO provides users with more refined investment analysis services through a "research-oriented" AI agent. Its core functions include automatically interpreting candlestick charts, assisting with technical analysis, evaluating whether a project has Rug risk, and generating information summaries similar to research reports. This AI-driven smart invest-research model lowers the analysis threshold for users, enabling investors to more efficiently gain market insights and provide robust support for decision-making.

4, VaderAI: AI Agent Investment DAO

VaderAI aims to become the "BlackRock" in the Agentic economy, attracting and expanding to its followers through its autonomously trading AI Agent token. The platform profits from investments and airdrops the profits to holders and followers, building a multifunctional AI Agent investment ecosystem. Its core goal is to establish itself as a leading AI Agent investment DAO management platform, driving industry innovation and scalability.

VaderAI drives the integration of technology and capital through a multi-agent system, aiming to build 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 distributed computing, agents can also reinvest in research and development, driving the platform's continuous development.

Furthermore, VaderAI employs an innovative token incentive mechanism to provide investors with B2B tool optimization, enhancing the platform's commercial application value. The platform also shares GP/carry profits with holders, further solidifying investor engagement and interest-sharing mechanisms, making VaderAI not only an investment platform but also a multi-win ecosystem that empowers agents and investors.

Five, Content & Creator

Whether in writing, editing, or visual design, AI can provide personalized creative output based on user needs, helping creators save time, increase productivity, and stand out in a competitive market. The platform's goal is to provide content creators with an intelligent and convenient creative assistant, driving innovation and development in the content industry.

5. ZEREBRO: AI Art Creation and Content Generation

ZEREBRO is a blockchain-based cross-chain natural intelligence autonomous AI agent focusing on art creation and content generation. Its innovation combines decentralized validation, meme generation, NFT minting, DeFi applications, and more, showcasing strong versatility and execution capabilities. ZEREBRO has successfully operated an Ethereum mainnet validation node and sold artwork on Polygon, accumulating significant assets for its economic foundation.

ZEREBRO is also dedicated to building a decentralized computing network and implementing MEV optimization strategies to ensure economic and technical sustainability. It is not just a technical tool but an exploration of agent technology's deep involvement in blockchain operations, economic models, and governance. ZEREBRO drives its value proposition in the decentralized ecosystem through multiple dimensions.

The ZEREBRO token serves two main purposes: as a content interaction reward, where token holders can earn rewards by engaging with decentralized content on social platforms, and as a community development tool to reward ecosystem participants actively engaged in content creation, staking, governance, and more, further enhancing community activity and engagement.

6. Gaming & Agentic Metaverse

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

6. ARC: AI Solution Provider

ARC addresses player liquidity issues in indie games and Web3 games through AI technology. The project has evolved from a single-game studio (AI Arena) to a comprehensive AI solution provider, introducing ARC B2B and ARC Reinforcement Learning (ARC RL). ARC B2B is an AI-driven game development toolkit (SDK) that seamlessly integrates into various games, offering developers an intelligent gaming experience. ARC RL leverages crowdsourced game data to train "super-intelligent" game agents through reinforcement learning to enhance gameplay and sustainability. ARC's business model is deeply tied to integrated game studios, with revenue streams including token distribution in Web3 games and performance-based royalty payments, while establishing a cross-game-type generalized AI data repository to drive the training and evolution of universal AI models.

The application of ARC's technology covers multiple core modules. AI Arena is a cartoon-style AI competitive game where players train AI warriors to fight, 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, with ARC handling backend data processing, training, and deployment. ARC RL improves AI training efficiency through offline reinforcement learning, allowing agents to learn from human player data to provide more natural and challenging game opponents. ARC's AI model architecture includes feedforward neural networks, tabular agents, hierarchical neural networks, etc., to adapt to the interaction requirements of different types of games while optimizing state space and action space to ensure a smooth and intelligent gaming experience.

ARC's market covers two major areas: independent games and Web3 games, helping developers address early player liquidity issues and enhance the long-term attractiveness of games. The core team members have rich experience in machine learning and investment management. In 2021, ARC received a $5 million seed round led by Paradigm and another $6 million follow-up financing in 2024. ARC's native token NRN has undergone a transition from a single-game economy (AI Arena) to a platform economy, adding integrated revenue, Trainer Marketplace fees, and ARC RL participation staking demand-driven factors to ensure the token's sustainability and value growth. Through a crowdsourced data contribution mechanism, ARC RL achieves multiplayer collaborative training, promoting the intelligent evolution of AI agents, further strengthening the vitality and competitiveness of the game ecosystem.

Seven, Framework & Hubs

When developing an AI Agent in the cryptocurrency field, many frameworks, while suitable for basic projects or toy-level applications, often expose issues of insufficient customization and overly abstract complexity in actual product development, requiring developers to not only spend additional effort debugging but also find it difficult to flexibly expand and apply. The core pain points that an excellent Agent framework needs to address include: comprehensive support for on-chain operations, efficient integration of on-chain data, DeFi automation, NFTs, and other key application scenarios' APIs; multi-platform compatibility, supporting major blockchains and social platforms to achieve user operation integration; modularity and flexibility, abstracting basic functions such as vector storage, LLM model switching, allowing developers to adapt to different needs flexibly, and avoiding repetitive development; memory and communication capabilities, although some frameworks invest heavily in enhancing these capabilities, excessive sophistication may not be practical at the current stage, instead adding complexity.

Below is a detailed comparison of the mainstream cryptocurrency AI Agent frameworks in various dimensions of the market.

7. Eliza ($AI16Z): AI Agent Framework

Eliza ($AI16Z) leads the AI agent market with approximately 60% market share and a robust TypeScript ecosystem, attracting numerous developers. Its GitHub project has accumulated over 6,000 Stars and 1.8K Forks, demonstrating high community engagement. Eliza is known for its multi-agent system and cross-platform integration, supporting mainstream social platforms such as Discord, X (Twitter), and Telegram, making it a key player in social AI and community AI. With its wide ecosystem foundation, Eliza excels in social interaction, marketing, and AI agent development.

On the technical architecture front, Eliza features multi-agent system capabilities, allowing different AI roles to share a runtime environment for more complex interaction patterns. Its Retrieval-Augmented Generation (RAG) technology gives AI long-term contextual memory, enabling consistency in continuous conversations. Moreover, the plugin system supports extensions like voice, text, and multimedia parsing, enhancing application scenario flexibility. Eliza is also compatible with multiple LLM providers such as OpenAI and Anthropic, delivering efficient AI computing capabilities whether in the cloud or on-premises. With the launch of the V2 message bus, Eliza's scalability will be further optimized, suitable for medium to large-scale social AI applications.

Despite Eliza's strong performance in the market, it faces certain challenges. Its multi-agent architecture may introduce complexity issues in high-concurrency scenarios, increasing system resource overhead. Additionally, the current version is still in an early development stage, 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 ongoing community contributions and the release of the V2 version, Eliza is expected to achieve further breakthroughs in scalability and stability.

8. GAME ($VIRTUAL): AI Agent Framework

GAME ($VIRTUAL) focuses on the game and metaverse core track, significantly lowering the developer threshold with low-code/no-code integration, allowing rapid building and deployment of intelligent agents. Leveraging the $VIRTUAL ecosystem, GAME has formed a strong developer community, accelerating product iteration and ecosystem expansion. Its core strength lies in providing efficient game AI solutions, making features like procedural content generation, dynamic NPC behavior adjustment, and on-chain governance more easily implementable.

In terms of technical architecture, GAME adopts an API + SDK model to provide a convenient integration method for game studios and metaverse developers. Its agent prompting 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, giving them greater adaptability in complex game environments. Furthermore, GAME also supports blockchain integration, enabling decentralized agent governance and on-chain wallet operations, giving it a unique advantage in the Web3 gaming domain.

GAME has been optimized for high-concurrency gaming scenarios and performs well in handling game engine constraints. However, its overall performance is still affected by the complexity of agent logic and blockchain transaction costs, which may pose a challenge to real-time interactivity. Additionally, as an AI agent framework focused on gaming and the metaverse, GAME has limited applicability in other domains. Moreover, the complexity of blockchain integration still needs to be optimized to reduce development costs and further attract a more extensive developer community.

9. Rig ($ARC): AI Agent Framework

Rig ($ARC) holds a 15% market share in the enterprise AI agent market, with a high-performance and modular architecture based on the Rust language. This architecture enables Rig to perform excellently in high-throughput and low-latency scenarios, particularly suitable for high-performance blockchain ecosystems like Solana. With robust system stability and efficient resource management, Rig has become an ideal choice for on-chain financial applications, large-scale data analytics, and distributed computing tasks. Its architecture design emphasizes scalability, allowing enterprise users to flexibly deploy AI agents in complex data environments to improve computational efficiency.

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

Rig leverages Rust's asynchronous runtime to achieve outstanding concurrency performance, scaling to high-throughput enterprise workloads. However, Rust itself has a steep learning curve, which may pose a certain entry barrier to some developers. Additionally, Rig's developer community is relatively small, and ecosystem drive still needs strengthening. Nevertheless, with the growth of Web3 and high-performance computing demand, Rig still has broad market potential and is expected to further increase market penetration through optimizing developer experience and enhancing community building in the future.

10. ZerePy ($ZEREBRO): AI Agent Framework

ZerePy ($ZEREBRO) holds a 5% market share in the creative content and social media automation field, with a total market value of $3 billion. Its core strength lies in a community-driven innovative ecosystem, allowing it to build a loyal user base in applications such as NFTs, digital art, and social content automation. ZerePy lowers the barrier to entry for AI agents, enabling content creators and community managers to easily deploy intelligent agents for automated content creation, social interaction, and community management, enhancing user engagement and content influence.

Technically, ZerePy is built on the Python ecosystem, providing a friendly development environment for AI/ML developers. Leveraging the modular Zerebro backend, it enables autonomous social task agents. Its social platform features optimize Twitter-like interactions, allowing agents to automate tasks such as posting, replying, and retweeting, enhancing social media automation capabilities. Furthermore, ZerePy's lightweight design makes it more suitable for individual creators and small community AI agent needs without incurring high computational costs.

ZerePy excels in social interaction and creative content generation but its scalability is more geared towards small-scale communities rather than high-intensity enterprise tasks. Additionally, due to its focused application scope, its applicability outside the creative domain still needs further validation. For scenarios requiring more complex creative output, ZerePy may require additional parameter tuning and model optimization to meet broader market demands. As the creative economy evolves, ZerePy is poised to further expand its application scenarios in NFT generation, personalized social agents, and more.

8. AI Launchpad

AI Launchpad not only provides emerging projects with a customized growth path covering technical support, fundraising, marketing, and opportunities for collaboration with industry experts but also helps projects rapidly 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. This platform enables each AI agent to have its dedicated token, creating a decentralized ecosystem. Users can not only collectively own these agents but also interact with AI-driven assets. The platform supports agent autonomous interactions on social media platforms such as Twitter, Discord, and Telegram and offers on-chain wallet management functionality, greatly enhancing its usability in various application scenarios.

The business model of vvaifu.fun is based on its unique tokenomics. The platform's main token, $VVAIFU, is the first AI agent token launched on the Dasha platform, featuring deflationary properties. Whenever an agent is created or a feature is unlocked, a certain amount of $VVAIFU is burned. 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 feature unlock, and more. Each launched agent also allocates 0.90% of new agent tokens to the community fund or directly into the team treasury to promote community participation and ecosystem development.

The platform's community engagement mechanism enhances user interaction and governance. Token holders can accumulate 0.90% of the agent launch supply in a community wallet and vote on the use of these resources. vvaifu.fun has also set the platform's transaction fee at 0.009 SOL, providing sustainable economic support for the platform's operation. Through these mechanisms, vvaifu.fun provides a comprehensive decentralized interactive platform for AI agent creators and users, driving not only the development of creative projects but also incentivizing active participation from the global community.

12. Clanker: AI Response Bot

Clanker is an AI response bot based on Farcaster, designed specifically for users to create and deploy memecoins and tokens. Through this platform, users can easily create their own token by interacting with Clanker. Users simply need to tag @clanker on Farcaster, informing the bot of the desired token and providing 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, as users need to manually add liquidity to price the token.

The underlying technical architecture of Clanker operates by combining Next.js middleware with large language models (LLMs) such as Anthropic's Claude or ChatGPT. When a user initiates 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 showcases how Clanker leverages AI technology to streamline the token generation and deployment process for users, effectively 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 the decentralized exchange. This process has accelerated the issuance of memecoins and tokens and supports the ecosystem by providing strategic value through components such as Telegram bots, DEXs, and aggregators, thereby driving on-chain transaction volume growth. With the increasing number of tokens, Clanker has contributed to a significant increase in transaction volume, enabling users to take advantage of low transaction fees and fast confirmation times, driving the circulation of on-chain assets like Solana and Base.

Key Takeaways

The AI Agent project's core is driven by technology and infrastructure, utilizing advanced programming languages and innovative algorithms to ensure efficient operation and support scalable expansion. Simultaneously, high-performance blockchain platforms provide outstanding transaction processing capabilities and cross-chain compatibility, enabling AI agents to seamlessly interact across different chains, driving the continuous optimization and upgrade of the technical foundation.

Payment and transaction infrastructure are key pillars for the AI Agent ecosystem's development. A stablecoin payment system safeguards transaction stability and liquidity, enhancing the interaction efficiency between AI agents and users. Decentralized autonomous trading systems eliminate human intermediaries to achieve more efficient and secure automated trading. In addition, innovative reward and governance mechanisms such as "proof of contribution" and "proof of collaboration" promote AI agent collaboration, resource sharing, and ensure long-term ecosystem health through a sound governance system.

Outlook and Challenges

The necessity of AI Agent tokens is often questioned mainly because they do not directly enhance the agent's functionality or bring significant advantages. Many view AI Agent tokens as similar to tokens in Web3 games, which may not necessarily provide substantial assistance to the project's core functionality. Therefore, some investors may overlook the actual value of these tokens due to blindly following the AI trend, leading to high risks, including potential scams. For these projects, some believe that they attract unsuspecting investors by masking legitimacy, especially compared to meme coins, where the tokens behind them may promise too many unrealized features.

If projects prioritize tokens as the primary driver, it may result in sacrificing core functionality and user experience, especially in non-gambling games and services. Tokens should be complementary elements rather than the predominant factor. Many successful projects have demonstrated that truly effective applications should focus on user experience, creating high-quality products, rather than solely relying on a token's economic incentive mechanism to attract users.

The fusion of AI and DeFi will be a significant future trend, with an estimated 80% of DeFi transactions being completed by AI agents, and proponents like Modenetwork and Gizatech are actively driving this development. Additionally, the role of AI agents in protocol governance will further expand, potentially leading to AI-driven governance attacks. Moreover, security-focused AI agents are expected to play a crucial role in protecting protocols from attacks, similar to the protection features offered by HypernativeLabs and FortaNetwork. As infrastructure continues to expand, the development of Trusted Execution Environments (TEE) and the central role of decentralized computing will enhance the resilience of AI agents. Furthermore, the surge of AI data markets will drive the growth of data payments between AI agents, with projects like Nevermined.io laying the foundation for this.

Disclaimer

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