8. How AlphaScope Works

The AlphaScope research pipeline can be understood in five stages.

Stage 1: Data Collection

The platform gathers data from supported on-chain environments, including transactions, wallets, token transfers, liquidity pools, contract interaction patterns, and holder distribution metrics. Additional off-chain contextual layers may also be included, such as social signals or narrative momentum indicators.

Stage 2: Signal Detection

The system scans for pre-defined and adaptive patterns associated with high-potential early-stage opportunities or elevated risk. These signals may involve capital flows, unusual wallet activity, sudden liquidity changes, or emerging ecosystem interactions.

Stage 3: AI Interpretation

The AI layer interprets detected signals in context. Instead of simply flagging volume or holder changes, it evaluates whether those changes are meaningful, suspicious, organic, concentrated, accelerating, or likely narrative-driven.

Stage 4: Scoring and Ranking

Projects are ranked using an internal multi-factor framework. While exact model parameters may evolve over time, the system may evaluate factors such as:

wallet quality, distribution health, liquidity structure, on-chain growth velocity, behavioral consistency, risk markers, and early narrative potential.

Stage 5: User Delivery

Insights are presented to users through dashboards, alerts, research reports, premium modules, and future API interfaces. Access is determined by wallet connection and $ASCP-based eligibility.