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City of Paris

An AI-driven system that digitizes and processes Paris’s participatory budgeting ballots, combining computer vision and automation to deliver faster, more transparent results
CITY OF PARIS -Case Studies

Development of a computer-vision–based system to automatically digitize, validate, and process participatory budgeting ballots for the City of Paris. The solution enables the city to efficiently handle large volumes of paper and online votes, ensuring transparency and speed in final tallying.

Overview

Industry : Ai

Location : France

Company Size : 5000+

Solutions : Al Consultation

Team : Pierre-Louis Guhur

Website link : https://participedia.net/case/participatory-budgeting-in-paris-france?utm_source=chatgpt.com

Scaling Democratic Participation

Ensure fair and accurate counting of participatory budgeting votes using Majority Judgment methodology. Blend digital ballots with automated paper ballot recognition, creating a seamless unified dataset.Reduce human error, accelerate tallying, and support the city’s ambition of scaling one of the world’s largest PB programs.
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Development

Stack : Python (ML & CV frameworks such as TensorFlow / PyTorch) , OpenCV / Tesseract for OCR and image preprocessing, PostgreSQL / SQL database for vote storage and aggregation, Web frontend for monitoring and result visualization (React / Vue).

Integrations : Integration with the City of Paris PB online voting platform, APIs for vote tallying, auditing, and reporting, Secure export to the city’s open data systems and dashboards.

Automations : Real-time reconciliation of scanned ballots with online submissions.,Automatic detection and correction of ballot anomalies ,Audit trails to support transparency and public trust.

Team lead : Pierre-Louis Guhur

Results

4

Month to launch

--

NEW USERS

76%

Speed increase

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