How market data is handled

The platform relies on multiple operational inputs including listing feeds, market records, developer disclosures, and internal normalization layers. Each source has its own context, limitations, and confidence profile.

Before data reaches users, it passes through cleaning, matching, and normalization so projects, developers, and areas appear as coherent entities. This reduces duplication and keeps outputs reviewable.

Some values are published directly from a source, while others are derived from deterministic rules such as classification, timing, and confidence checks. Signals must pass quality controls before publication.

If coverage is incomplete, freshness is weak, or the linkage is not reliable enough, confidence may be reduced or some information may be withheld. The aim is to avoid false precision.

Retention depends on dataset type and sensitivity. Access to some layers is limited to authorized roles and processes, with operational logging for accountability where needed.