Intelligence without
unsupported certainty.
AEGIX is deterministic and evidence-backed. It converts observable public activity into structured intelligence, while making clear where evidence is weak or the picture is incomplete.
From signal to exposure.
Each stage is versioned and inspectable. Confidence is never a guess — it reflects data quality, sample adequacy, and semantic coverage.
- 01Signal↓
- 02Evidence↓
- 03Relationship↓
- 04Correlation↓
- 05Confidence↓
- 06Exposure
Correlation ≠ Ownership ≠ Identity
AEGIX reports observable relationships. It does not identify the person behind a wallet, and correlation is never proof of ownership.
How strong are the observed relationship signals.
How reliable the available evidence is.
AEGIX observed population ≠ global Solana
Population Commonality measures observations inside AEGIX's eligible dataset, subject to freshness and sample requirements. It never implies global chain frequency unless the backend genuinely measures it.
Common hub penalty
Shared popular hubs contribute less evidence than rare, distinctive relationships.
Common entity penalty
Interactions with widely-used entities are discounted as non-distinctive.
Population commonality
Overlap is weighted against the AEGIX-observed population, not the whole network.
Dust filtering
Negligible transfers are excluded so routine noise cannot inflate resemblance.
Sample adequacy
Results carry lower confidence when there are too few transactions to reason about.
Single-family caps
No single evidence family can dominate a conclusion.