How it Works

MetaLogic operates as a layered intelligence system that scans, analyzes, and categorizes new Solana-based token launches using a combination of blockchain data, heuristic filters, and AI meta-matching. Its primary goal is to surface tokens that align with emergent cultural trends and demonstrate early signs of organic momentum — while filtering out scams, honeypots, and low-quality launches.

Data Aggregation

MetaLogic pulls token data directly from trusted on-chain analytics providers like DexScreener. It fetches up to 500 of the most recent Solana token launches, including:

• Volume (24h)

• Market Cap

• Liquidity

• Price Change (24h)

• Launch Age (in hours)

• Contract activity

All tokens under review must pass minimum thresholds (e.g. price increase, market cap over $1M, and under 5 days old) before being included in leaderboards or meta match checks.

Meta Tagging Engine

After the tokens are ingested, MetaLogic’s AI engine assigns Meta Tags — high-level cultural or narrative categories that describe the theme or memetic identity of the token.

Examples of Meta Tags:

• Animal Meta – tokens referencing animals (e.g. Dog, Cat, Meerkat)

• AI Meta – tokens referencing artificial intelligence, AGI, etc.

• Political Meta – tokens named after politicians or political ideas

• Hype Meta – tokens with names like “100x,” “MoonShot,” “Next Big Thing”

• Utility Meta – tokens that include hints of tooling, bots, or platforms

This AI tagging process improves visibility for trend-based investing and provides context for what each token represents — something traditional metrics alone don’t capture.

Token Filtering

Once Meta Tags are applied, additional filters are used to narrow down the best candidates:

• Volume-to-Market Cap Ratio: Indicates organic interest

• Liquidity Strength: Helps detect rugs or weak launches

• Growth Trajectory: AI detects if the price movement is smooth, sharp, or manipulated

• Duplication Elimination: Ensures the same token doesn’t appear in both the “Leaders” and “Meta Matches” sections

Tokens that pass these filters are either:

• Shown in the Leaders section (top % gainers in last 48 hours)

• Or surfaced through the Meta Match engine (based on user interaction)

Interactive Discovery

Users can browse trending tokens, explore their associated meta categories, and click “Find Meta Matches” to discover related tokens in the same category. This creates a natural feedback loop between data discovery and AI-driven trend spotting — with a card-based UI optimized for both meme appeal and usability.