2. Weak Correlation Between AI and User Network Interaction Experience

The potential of AI in investment behavior extends beyond data analysis; it can also transform the way users interact with networks. However, at this stage, the interaction experience between AI and users in the Web3 ecosystem remains relatively weak, with many tools limited to passive responses. For example, traditional AI trading assistants primarily focus on executing commands, lacking deep interaction with users. This interaction mode fails to genuinely help users understand complex market dynamics or cultivate their investment decision-making abilities.

Additionally, the uniqueness of the Web3 user network presents new challenges for AI. Web3 emphasizes user autonomy and privacy protection, which conflicts with traditional AI models that require extensive data to optimize user experience. In this context, designing an AI interaction solution that balances user privacy with efficient interaction has become a key issue for the industry.

Breakthrough Direction： Omnipilot's solution lies in constructing a more intelligent and proactive interaction model. Through multi-modal intelligent information flow support, the platform can analyze diverse information encountered by users (such as text, video, and voice) and proactively provide personalized investment recommendations. Importantly, Omnipilot incorporates decentralization and privacy protection into its core design, allowing users to enjoy top-tier AI services while maintaining complete control over their data.