Abstract

Blockchain networks promise financial transparency, yet the raw data they produce — hex-encoded addresses, function selectors, wei denominations, and nested event logs — remains opaque to the vast majority of users. This paper presents a 10-stage decode pipeline architecture that transforms raw Ethereum transaction data into structured, human-readable intelligence. Combined with 25 deterministic safety signals and AI-powered narration, the system achieves 100% action classification accuracy across a 132-transaction benchmark while maintaining sub-2-second response times at a cost of approximately $0.001 per AI explanation.