If general AI is a 'versatile', FLock is an 'efficient assistant' for on chain operations. FLock achieves an accurate matching rate of 75.93% for feature calls, surpassing general models such as GPT-4o. Through decentralized training and collaboration with AI Arena, FLock breaks the monopoly of giants and creates the first 'AI DAO' economic system. Flock's four killer level application scenarios are unparalleled by humans in terms of improving work efficiency and risk control. Below is a brief description of the role, advantages, and future application uses of FLock application scenarios. 1) Real time DeFi decision-making One of the biggest challenges faced by liquidity providers in the DeFi field is impermanent losses, especially in markets with price fluctuations. The FLock Web3 proxy model quickly generates position adjustment recommendations by monitoring the liquidity pool data of Uniswap V3 in real-time, such as price ranges, trading volumes, and fund utilization rates, combined with historical trends on the chain and external market signals (such as ETH/BTC price fluctuations). For example, when FLock detects a price deviation and an increase in a certain pool due to this reason, it immediately suggests transferring funds to a better range or different pools, and even suggests exiting and locking in profits. Future application cases: LP users input "Optimize Uniswap V3 Position" through FLock's mobile DApp: The model analyzes their position within seconds and, based on current market conditions, outputs a recommendation: "Reduce 50% liquidity from ETH-UDT 0.05% fee pool rate to 0.3% fee pool rate, expected to reduce impermanent losses by 12% and increase annualized returns by 8%." For professional market makers, FLock also integrates API to provide real-time monitoring and automated execution of batch pools, further improving fund efficiency. effect: FLock transforms complex on chain data into insightful decision support, allowing retail investors to pay attention to the market like professional institutions, reduce DeFi participation, and improve revenue stability. 2. Cross chain asset tracking With the increasing use of cross chain bridges to transfer assets, the complexity and potential risks of transaction paths (such as funds being cleaned by coin mixers or hacked) have become security pain points. The FLock Web3 proxy model integrates multi chain data to track the complete flow path of assets with just one click. For example, if a user inputs a hash that requires cross chain transactions, FLock can generate a visual report within the number, annotate each address where funds flow in seconds, and use AI to identify abnormal patterns - such as associations with known coin mixers (such as Tornado Cash) or high-risk wallets. Future application cases: When users use FLock's browser plugin to transfer assets across chains: After entering a transaction, the plugin immediately pops up a warning: "This transaction path involves 3 intermediate addresses, one of which is associated with a coin mixer, with a risk rating of 80%." For enterprise users (such as wallet service providers or institutional audit processes), FLock can analyze thousands of cross chain transactions in bulk, generate risk assessment reports, and help optimize compliance. effect: FLock enables ordinary users to easily audit cross chain transaction security, while enterprises can significantly improve asset management efficiency, prevent financial losses and regulatory risks. 3) Smart Contract Insights In Web3, the smart contracts of emerging projects such as Memecoin often conceal risks (such as developer backdoors and the possibility of pulling). The FLock Web3 proxy model quickly extracts key information by analyzing contract code and on chain transaction data. For example, if a user inputs the contract address of a memecoin, FLock will scan its permission settings (such as whether it can be upgraded, whether there are relevant functions), early transaction records (whether there is a mouse warehouse storing tokens), and the movements of smart money (such as whale wallets), and finally generate a concise report: "Contract owners can freely issue tokens, 20% of the supply is concentrated in 3 addresses, and smart money has started to sell". Future application cases: In the future, FLock may be embedded in decentralized trading platforms: click on "FLock Insights" before buying, receive risk warnings within 5 minutes, and avoid stepping on landmines. For on chain detectives or retail investors, FLock can still provide subscription services to keep up with real-time analysis of popular memecoin movements and seize short-term arbitrage opportunities. effect: FLock threatens ordinary users with professional level contract analysis capabilities, reduces investment due to inaccurate information during weekly decision-making time. 4. Research on Automation Chain VC institutions and on chain researchers need to quickly assess the potential of emerging protocols such as L2 and DeFi projects, but manually collecting on chain data remains laborious. The FLock Web3 proxy model aggregates data from multiple sources. For example, when entering a new protocol name, FLock can output a draft within minutes, including core indicators such as lock up volume changes, active address numbers, competitive comparisons, and potential risks. Future application cases: When VC uses FLock's dashboard: enter "Analyze Arb Ecological New Project", the model automatically captures data from 10 protocols, generates a report, and marks "Project X has a user proportion of 300%, but 75% of tokens are controlled by the team, it is recommended to observe the channel". For independent researchers, FLock can output a preliminary research report in Markdown format, which can be directly used for article publishing or internal discussions. effect: FLock significantly reduces investment research time, allowing VCs and individuals to seize Web3 investment opportunities faster while improving decision quality. The FLock Web3 proxy model deeply combines AI customization with Web3's decentralized functionality through four killer features, bringing the following core values to users: 🔸 Efficiency improvement: From minute level contract analysis to automated research and development, saving time and costs. 🔸 Risk prevention and control: Real time monitoring and precise insights to reduce unpredictable losses and security risks. 🔸 Inclusiveness: Delegate professional tools to individual investors and narrow the information gap with institutional players. 🔸 Future orientation: Provide infrastructure for developers and ecosystems, and incubate more Web3 AI applications. These features not only address existing pain points, but also lay an intelligent foundation for the future Web3 ecosystem.