Beyond Documentation
While traditional human rights monitoring focuses on cataloging past events, PrisonerWatch utilizes data science to identify emerging threats. By aggregating data from organizations like OVD-Info and Memorial, we not only create a unified database but also train machine learning models to detect patterns of repression.
Our platform calculates individual risk scores for torture and urgency, maps judicial complicity networks, and provides automated legal support tools for immigration lawyers and human rights defenders.
Technical Capabilities
Built with advanced machine learning pipelines to provide actionable intelligence
Predictive Forecasting
Prophet-based time series modeling that forecasts arrest trends up to 90 days in advance, allowing organizations to prepare resources.
ML Risk Assessment
XGBoost classifiers analyze demographic and legal data to calculate the probability of torture and high-urgency status for every prisoner.
Legal Aid Automation
AI-powered tools that generate affidavit support drafts and sanctions dossiers by cross-referencing case history and country conditions.
Network Topology
Graph-based community detection identifying clusters of cases connected by shared locations, criminal articles, or legal actors.
Semantic Topic Modeling
Non-negative Matrix Factorization (NMF) extracts evolving narrative themes from case descriptions to understand prosecution strategies.
Public API
RESTful API with authentication for researchers to access cleaned, translated, and geo-coded datasets programmatically.
Data Pipeline
Automated Scraping
Daily synchronization with source databases to ensure real-time accuracy
Geospatial Coding
Automatic conversion of arrest locations into coordinates for heat mapping
Neural Translation
Seamless Russian-to-English translation of legal summaries and charges
Entity Extraction
Identifying and linking specific judges, prosecutors, and surveillance vendors