Reality Check - Explainable Manipulation Risk Platform

Challenge

Editorial and policy teams needed a scalable, explainable way to detect manipulation tactics in high-volume digital text.

Approach Timeline

1. 1

   Designed a hybrid scoring engine combining deterministic rule checks with transformer-based contextual interpretation.

2. 2

   Built a React + FastAPI review interface with transparent rationale display for each risk category.

3. 3

   Implemented calibrated confidence and exportable audit reports for policy and governance workflows.

Outcome Highlights

• Reduced analyst review friction through prioritized risk queues.
• Improved confidence in moderation decisions with explainable evidence trails.
• Enabled reusable reporting for enterprise and policy stakeholders.

Technology

React | FastAPI | Python | NLP