OrcaSignal v2.0
Rule-based on-chain analytics to surface concentration, distribution, and manipulation risk.
Project Description
OrcaSignal v2.0 is an explainable on-chain analytics platform focused on market integrity. Instead of black-box ML or address deanonymization, it uses transparent, rule-based signals derived from on-chain data to surface risk indicators such as token concentration, holder distribution shifts, and abnormal flow patterns.
The goal is to help traders, protocols, and researchers understand when price action may be driven by structural risk rather than organic demand. OrcaSignal emphasizes reproducibility and clarity — every signal is traceable back to verifiable on-chain events. This makes it suitable for pre-trade risk assessment, monitoring DeFi markets, and building safer execution or liquidity strategies on top.
How it's Made
The project is built using a modular indexing and analysis pipeline over Ethereum on-chain data. Raw transaction, transfer, and holder data is aggregated off-chain and processed through deterministic rule-based heuristics to compute risk signals such as concentration scores, distribution entropy, and abnormal flow flags.
A lightweight smart contract layer is used only where on-chain verification or anchoring is meaningful, while analysis and visualization are handled off-chain for flexibility and performance. The frontend presents signals with clear explanations of how each metric is derived, avoiding opaque models and prioritizing interpretability.
