Revisor is an AI-driven software designed to monitor electoral processes by accurately counting voters and ensuring compliance with electoral procedures. Leveraging neural network technology, it analyzes video recordings from polling stations to detect ballot boxes, track voter movements, and identify voting events. This system offers a cost-effective and scalable solution, enabling comprehensive election observation across numerous polling stations without the need for physical poll watchers. With up to 98% accuracy, Revisor provides reliable and timely insights into voter turnout and potential irregularities, enhancing the integrity and transparency of elections. Key Features and Functionality: - Ballot Box Detection: Identifies and outlines ballot boxes in video footage, determining their type and location. - Voter Counting: Accurately counts the number of voters casting ballots, facilitating precise turnout analysis. - Anomaly Detection: Compares actual voter turnout with official results to identify discrepancies and potential instances of electoral fraud. - Customizable Training: Adaptable neural network that can be trained for various voting procedures and electoral systems across different countries. - Post-Election Analysis: Capable of processing video recordings immediately after elections or even years later, ensuring long-term accountability. Primary Value and Problem Solved: Revisor addresses the challenges of ensuring fair and transparent elections by providing an automated, scalable, and cost-effective method for monitoring polling stations. By eliminating the need for extensive human resources, it allows for comprehensive coverage of electoral processes, promptly identifying irregularities and enhancing public trust in election outcomes. Its high accuracy and adaptability make it a valuable tool for election authorities, observers, and investigative bodies committed to upholding democratic integrity.