WALPHA is a layered cognitive intelligence system for the crypto trenches. Each layer has a distinct responsibility so that collection, identity, memory, analysis, verification and delivery do not collapse into one opaque model call.
System flow
1. Source ingest
X/Twitter events arrive through controlled webhook collection and targeted enrichment. The original event is retained before downstream interpretation.
2. Canonical evidence
Posts, authors, timestamps, media and source references are normalized into durable records. Duplicate deliveries do not become duplicate evidence.
3. Entity and relationship resolution
Deterministic parsing identifies explicit accounts, tickers and contract-shaped identifiers. Contextual analysis proposes projects, narratives and relationships. Proposed links remain distinguishable from resolved identity.
4. Evidence graph and temporal memory
Accounts, projects, assets, claims and narratives are connected through typed, time-qualified relationships. WALPHA can recall prior evidence without allowing future knowledge to leak into an earlier event-time judgment.
5. Cognitive reduction and narrative formation
The Brain compares fresh facts with eligible prior memory. It records convergence, recurrence, contradictions, mood, rotation, project positioning and versioned narrative state. A model may interpret a compact evidence pack, but canonical facts and deterministic measurements remain separate.
6. Enrichment and on-chain verification
Metadata, market snapshots, holder state and wallet intelligence are joined by typed contracts. These services provide confirmation or counter-evidence; they do not rewrite the source post or turn missing coverage into a negative fact.
7. Temporal intelligence and outcomes
Windowed aggregation measures velocity, independent author breadth, recurrence, convergence and cooling. Event-time checkpoints measure later outcomes without confusing asset movement with author profit or thesis correctness.
8. Interpretation, review and delivery
Reports, alerts, Telegram delivery and future publishing workflows consume the same traceable entities, theses and sources. Material changes create new states rather than silently overwriting the earlier interpretation.
9. Reputation and feedback
Measured outcomes, corrections and reviewed relationships can change versioned participant, relation and narrative context. The next analysis may use that memory only when it predates the new evidence window. This closes the learning loop without allowing future results to rewrite past decisions.
Separation of concerns
Collection does not decide identity. Identity resolution does not invent market facts. Scoring does not erase source lineage. Delivery does not change the underlying evidence. These boundaries are what allow WALPHA to grow across networks and channels without losing trust.