What is Revisor?

Revisor is a neural network-based monitoring system designed for electoral oversight. It efficiently counts actual voter turnout and monitors compliance with electoral procedures using video recordings. The system employs advanced capabilities to learn and recognize physical objects, track movements, and detect voting events, achieving an accuracy rate of 98% under ideal conditions.

Users can deploy Revisor at scale, utilizing thousands of poll watchers across all polling stations in a constituency at a fraction of traditional observation costs. The tool is adaptable, allowing customers to train the neural network to operate with various voting procedures and electoral systems tailored to different countries.

⭐ Key features

Revisor core features and benefits include the following:

✔️ Neural network-based monitoring.
✔️ Video recording analysis.
✔️ Object recognition and tracking.
✔️ Scalable deployment with multiple poll watchers.
✔️ Adaptable training for various voting procedures.

⚙️ Use cases & applications

✔️ Monitor voter turnout at large-scale elections using Revisor to ensure accurate counts while significantly reducing the costs associated with traditional poll watching methods.
✔️ Utilize Revisor's adaptive neural network capabilities to ensure compliance with local electoral procedures across various jurisdictions, thereby enhancing trust in the electoral process.
✔️ Conduct thorough post-election analyses by reviewing retained video data to identify discrepancies in official turnout figures and supporting accountability in electoral management.