Revisor: Voter Monitoring Software
Revisor helps election observation missions and investigative journalists monitor voter turnout. It is designed for organizations that need to verify official election results against video evidence.
At a glance
- Category
- Browse Other tools
- Best for
- Election observation missions, Investigative journalists
- Pricing
- Pricing was not clearly available from the provided evidence. Buyers should confirm current pricing on the vendor website.
- Key use cases
- Electoral Auditing, Investigative Journalism, Election Observation, Compliance Monitoring
- Official website
- Visit Revisor official website
Revisor is a software package designed to analyze video recordings from polling stations. Using neural networks, the system is designed to recognize physical objects and track movements to help determine how many people cast ballots.
The tool is intended for election observers and journalists conducting electoral investigations. It focuses on detecting ballot boxes and counting turnout to help identify discrepancies between actual numbers and officially published results.
Because it operates on video records, results may be obtained immediately after an election or for retrospective audits. The software is a trainable system, which may help it adapt to different voting procedures and electoral systems across different countries.
Buyers should confirm the placement and quality of camera setups, as the accuracy of the voter count is dependent on the relative position of the cameras and ballot boxes.
Key Features
AI Video Analysis
Uses neural networks to recognize physical objects and track movements within polling station recordings.
Voter Turnout Counting
Counts the number of voters who cast ballots, with reported accuracy up to 98% depending on camera positioning.
Ballot Box Detection
Identifies ballot box outlines, types, and locations within video records.
Discrepancy Reporting
Compares actual voter turnout against officially published results to help identify potential falsifications.
Violation Detection
Supports the identification of certain types of voting violations and suspicious activities.
Trainable Neural Network
Can be trained to work with various election types, procedures, and electoral systems globally.
Use Cases
Electoral Auditing
Comparing official turnout figures with AI-calculated voter counts to identify falsified results.
Investigative Journalism
Processing polling station video to find evidence of voting irregularities.
Election Observation
Using digital monitoring to cover polling stations in a constituency.
Compliance Monitoring
Monitoring video records to detect specific voting violations and electoral procedure breaches.
Best For
- Election observation missions
- Investigative journalists
Pricing
Pricing was not clearly available from the provided evidence. Buyers should confirm current pricing on the vendor website.
FAQ
What does Revisor do?
- Revisor uses AI-enabled video analysis to count actual voters at polling stations and monitor compliance with electoral procedures.
Who is this software intended for?
- It is designed for election observation missions and journalists conducting electoral investigations.
How accurate is the voter counting?
- The system has achieved up to 98% accuracy in testing, depending on the relative position of the cameras and ballot boxes.
Can it be used for elections in different countries?
- Yes, it is a trainable neural network that can be taught to work with different voting procedures and electoral systems globally.
Source category: Other
Source subcategory: Analytics & Reporting
More tools in Other
Other published listings in the Other category.
More tools tagged “Analytics and Reporting”
Related listings that share the same software type tag.
Categories
Software Type
How AI is used
Revisor is a neural network-based video analysis tool used by election observers and journalists to count voters and monitor electoral compliance. It supports the identification of turnout discrepancies by comparing video data to official results. System accuracy is dependent on camera placement.
Pros & Cons
Pros
- Capable of processing large volumes of video data
- Adaptable to different international electoral systems
- Supports retrospective analysis of recordings
- High reported accuracy when cameras are correctly positioned
Cons
- Accuracy depends on camera and ballot box positioning
- Users must manually investigate the specific cause of discrepancies flagged by the system
- Requires existing video recordings to function
