Computed data

Pond3r uses a combination of on-chain data, social data, and price data to compute the data that is used to create computed datasets.

How It Works

Our computed data pipeline works by:

  1. Collecting raw data: We aggregate data from multiple sources including on-chain transactions, price feeds, and social platforms
  2. Processing and transforming: Raw data is cleaned, normalized, and structured for efficient querying
  3. Calculating metrics: We compute complex metrics like APYs, correlations, and trends that would be inefficient to calculate in real-time
  4. Storing in optimized format: Processed data is stored in a format optimized for quick retrieval based on natural language queries
  5. Regular updates: Computed datasets are updated at regular intervals to ensure data freshness

Supported Computed Data

Pond3r provides the following computed datasets:

DatasetDescriptionUpdate Frequency
ApysApys for most of the yield protocolsDaily
Social SentimentAggregated sentiment analysis from Farcaster and other social platformsDaily
Most trade tokens on FarcasterMost traded tokens on FarcasterDaily

Our AI will automatically determine when to use computed data versus fetching real-time data directly from on-chain sources.

Benefits of Using Computed Data

  • Faster Response Times: Pre-computed metrics avoid complex calculations during query time
  • Historical Trend Analysis: Access patterns and changes over time that wouldn’t be visible from current state alone
  • Cross-Protocol Insights: Compare metrics across different protocols and chains standardized to the same methodology
  • Complex Calculations: Access metrics that require significant computation (e.g., correlation analysis, risk metrics)
  • Reduced On-Chain Load: Minimize the need for extensive on-chain queries for commonly requested data

If you need a specific computed dataset that isn’t currently available, please let us know through our Discord community. We regularly expand our computed data offerings based on user requests.