DeFi Analytics Problem

DeFi is experiencing significant growth, with a diverse range of tokens—spanning from meme tokens to utility tokens—being launched daily. On-chain trading via decentralized exchanges (DEXs) is also gaining momentum as users increasingly move away from centralized exchanges (CEXs). This shift highlights a strong preference within the crypto community for decentralization and direct asset control, driving the evolution of the financial landscape. However, on-chain active traders currently lack a comfortable platform to meet their daily trading needs, underscoring a critical area for development and innovation in the DeFi space.

A key aspect of Thoros.ai is the ability to synthesize and interpret large amounts of heterogeneous data. Such large amounts of data are naturally found in Web3 projects and can be categorized into on-chain, off-chain, and sentiment data:

• ● On-chain data includes transaction volume, active users, network fees, block information, smart contract interactions, events, liquidity pools, total value locked, token holder distribution, airdrops, and related metrics and offers insight into usage, scalability and economic health.

• ● Off-chain data covers metadata, user interactions, developer engagement, broader community activities, and auxiliary information stored outside the blockchain for size and privacy reasons and it offers clues about flexibility, data storage and overall chain performance. ● Sentiment data includes market sentiment and social media trends such as news outlets, blogs, forums, and even platforms such as Youtube, Telegram, Discord, etc. Sentiment analysis tools measure social volume, sentiment ratios, and influencer endorsements and allow to gauge community outlook and predict shifts in project trajectories. Social media trends are analyzed using natural language processing.

Taken together, this comprehensive data forms the backbone of our AI algorithm, which will help guide strategic decisions in the blockchain ecosystem.