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Scores & AI agents

How QQ Scores & AI Agents Work?​

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TLDR: Data → AI agents → Scores → Clear overview for your decisions.

  1. Data collection
    QQ Omega collects and organizes on-chain data such as holders, flows, liquidity, and token activity, as well as off-chain data such as products, documentation, news, and macroeconomic context.

  2. AI agents per area
    Data is grouped by category and fed into multiple, structured swarms of AI agents, each dedicated to a specific analytical area.

    Here are some examples:

    • Fundamentals swarm: one agent for team, one for product, one for security, and more.
    • Tokenomics swarm: one agent for buybacks, one for emissions, one for unlocks, one for utility, and more.

  3. From agents to scores

    • Each agent produces a sub-score based on its own metrics and evaluation rules.
    • Sub-scores are combined using different weights and normalization methods into a category score (for example, a Fundamentals Score).
    • All category scores are then aggregated into a global QQ score for each project.

  4. Continuous updates
    As new data becomes available, including on-chain movements, token unlocks, new partnerships, or changes in market sentiment,
    agents update their assessments and scores evolve over time.