๐ŸŽฏPaal AI Sniper

Overview

The Paal AI Sniper leverages Paal's exclusive AI technology to identify, assess, and suggest emerging tokens with growth potential. It relies on two main data sources for recommendations: Blockchain and Social data. Through rule sets and dynamic real-time data parameters, the AI conducts thorough analyses on both blockchain and social data, constantly refining its strategies. By learning from these inputs and results, the AI enhances its buying recommendations progressively.

Data Sources

Blockchain Data

The blockchain data component of the Paal AI Sniper includes various checks and metrics such as:

  • Scanning for newly listed token pairs.

  • Verifying if social media links are updated on platforms like Dexscreener, Dextools, CoinGecko, etc.

  • Assessing the status of liquidity (burned/locked).

  • Evaluating the amount in the liquidity pool.

  • Counting the number of holders.

  • Measuring the distribution among holders.

These data points contribute to calculating a Blockchain Score, which is then evaluated against a predefined threshold.

Social Data

The social data component involves analyses such as:

  • Text analysis of the projectโ€™s website using AI technologies.

  • Visual analysis of the project's website.

  • Statistical data and sentiment analysis from the projectโ€™s social media presence.

  • Influencer interaction and sentiment analysis on social media platforms.

These data points contribute to calculating a Social Score, which is then evaluated against a predefined threshold.

Machine Learning Integration

The Paal AI Sniper uses machine learning to learn from successful tokens that were previously alerted by the system. By analyzing the patterns and characteristics of these successful tokens, the AI continuously improves its predictive models. This learning process allows the AI to enhance its accuracy and effectiveness in identifying and recommending promising tokens over time.

Decision Process

The AI system combines the Blockchain Score and Social Score. If both scores exceed their respective thresholds, the AI triggers a buy recommendation, suggesting the purchase of a specified amount of the token.

Continuous Improvement

The Paal AI Sniper continually refines its analysis and recommendations by learning from new data inputs and the outcomes of its previous recommendations. This iterative process helps in enhancing the accuracy and effectiveness of its token buying strategies, ensuring that the system adapts to the ever-evolving cryptocurrency market.

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