Project Background

1.1.1 Challenges of Web3 industry

Web3 projects have faced criticism many times by both practitioners and users, saying that there is no real mass adoption within Web3 and that it does not address the needs of real users.

Currently, the entire crypto market has a market capitalization of $3.33T, with Bitcoin accounting for $2T, public chain ETH accounting for $404.65B, BNB at $99B, and SOL at $90.56B, the majority of the market capitalization is taken up by the infra layer, with the demand for the application layer not being opened up.

The last potential mass adoption of Stepn's peak market cap of $2.3B attracted a lot of web3 and non-web3 users, but the peak market cap lasted 1 month. The question remains: where is the next mass adoption?

AI and Web3 convergence holds the greatest potential for future mass adoption.

• Emerging Field: The combination of Web3 and AI is an emerging field that warrants significant attention.

• AI's Role: AI enhances productivity and addresses real user needs.

• Web3's Role: Web3 revolutionizes production relationships and introduces new business models and asset liquidity.

• The promise of Integration: The integration of Web3 and AI represents the most promising potential for achieving mass adoption, merging technological advancements with practical, real-world applications.

1.1.2 Challenges of Prediction Markets

Prediction markets face significant challenges that must be resolved to achieve sustainable growth and wider adoption:

Challenge 1: Centralization and Lack of Customization

Traditional prediction markets are often centralized, limiting user autonomy. Platforms dictate available prediction pools, leaving no opportunities for the mass to create markets that align with their interests or unique community needs. This centralization stifles creativity and engagement, restricting the potential for truly personalized and dynamic user experiences.

Challenge 2: Limited Earning Opportunities for Users

Existing prediction market platforms fail to provide meaningful earning opportunities for users. The majority of platforms are designed primarily to generate revenue for the platform operators, leaving participants with minimal returns. Without the prospect of sustainable profits, users lose motivation to remain active, leading to stagnation and undermining the platform's long-term viability.

For prediction markets to succeed, solutions must empower users to create their own markets while introducing revenue-sharing mechanisms that reward user participation and contributions. By addressing these core issues, prediction markets can foster deeper engagement, enhance user incentives, and lay the groundwork for sustainable ecosystems.

Therefore, Nextmate.AI is introduced.