The digital transformation of democratic institutions has reached a critical juncture where traditional centralized electronic voting systems (E-voting) are no longer sufficient to combat sophisticated cyber threats and internal administrative manipulation. This research introduces BlockVote, a holistic, decentralized voting architecture designed to solve the "Trust Deficit" in modern elections. The system pivots away from the vulnerability of central servers, utilizing a peer-to-peer Distributed Ledger Technology (DLT) to record votes as immutable transactions. A primary innovation of this project is the integration of a multi-modal identity verification suite. By combining *biometric fingerprint data* with *real-time AI-driven Facial Recognition, the system effectively eliminates the possibility of "Sybil attacks" or identity impersonation. To bridge the gap between complex blockchain operations and user accessibility, the platform incorporates a Text-based AI Bot. BlockVote provides a scalable solution for both small-scale organizational voting and large-scale national elections. The study evaluates the system based on three core metrics: cryptographic integrity, authentication accuracy, and user experience (UX) fluidity. The findings suggest that by decentralizing the "Source of Truth" and automating tabulation through Smart Contracts, we can achieve an electoral process that is transparent, verifiable, and entirely resistant to retroactive tampering.
