In Highlight: FORTAJUS-DH – Human Rights Monitoring System

FORTAJUS-DH stands out because it goes far beyond counting cases or simply checking compliance with international recommendations. From the very beginning, the team developed its own methodologies to translate abstract human rights obligations into concrete, measurable indicators. This makes it possible to see not only whether obligations are being fulfilled, but also “how they are applied in practice”.

The journey has been built in layers. The “first layer”, or the conceptualization phase, involves translating international standards into specific, measurable indicators. This requires careful interpretation, methodological rigor, and an understanding of how judicial processes actually work. Every indicator is designed to reflect meaningful actions derived from international obligations, not just data points.

The “second layer” focuses on the generation and extraction of information—a big-data phase that combines manual, artisanal work with partial automation. Here, we structure, validate, and process millions of judicial rulings using a hybrid approach, mixing traditional analysis with automated tools and language models. This isn’t just about efficiency; it’s about laying the foundation for future AI-driven insights. Once fully operational, these systems will be able to anticipate trends, detect risks, and support proactive human rights monitoring. All of this should lead to evidence-based decision making while crafting public policies within the Mexican judiciary.

Finally, the new system is connected to pre-existing systems and data bases through an API, which means that it doesn´t require additional inputs nor it pose new obligations for the personnel in charge of adjudicating cases.

In short, FORTAJUS-DH is both “methodology and innovation”: a carefully built bridge between human rights law, judicial practice, and the future of AI in monitoring.

Yes. FORTAJUS-DH has become a national reference point. Its methodologies are being explored for adaptation or replication in other government agencies, which could extend its impact beyond the Federal Judiciary. Its architecture, including APIs and interoperability standards, also allows potential integration with other platforms, paving the way for AI-driven monitoring systems that could analyze human rights data across institutions.

Take the prohibition of torture and other ill-treatment. FORTAJUS-DH tracks how courts apply procedural safeguards, like excluding evidence obtained under duress or ensuring proper conduct of hearings. By combining quantitative indicators with qualitative analysis of judicial reasoning, the system highlights patterns and gaps that might otherwise go unnoticed.

Looking forward, AI and machine learning will allow the system to process vast numbers of rulings efficiently, flag emerging risks, and generate predictive insights, making human rights monitoring more **proactive and anticipatory**. This approach could translate into amendments to our training courses or the development of new teaching methodologies, for example.

Primarily, internal actors within the Federal Judiciary use the system: policymakers, administrative units, and judicial managers. But its reach doesn’t stop there. The system also supports reporting to international human rights bodies and provides critical information for academics, civil society organizations, and experts interested in the practical implementation of human rights in Mexico.

Yes. The system is continuously evolving. We’re expanding the rights covered and refining our methodologies to improve both the precision and usefulness of the indicators.

One key focus is enhancing internal interoperability: connecting different systems within the Federal Judiciary to maximize the value of the information already available. This is about optimizing existing data flows, ensuring consistent and reliable information for monitoring, and making it easier for the institution to use the data in decision-making.

At the same time, we are preparing the foundation for AI and machine learning applications, particularly language models for automated extraction of information from judicial rulings. While full AI integration is a future goal, the current work ensures that all data is structured, accurate, and ready to support more advanced analytical tools.

In short, the emphasis is on making the most of internal information, improving analysis and reporting, and building the groundwork for smarter, AI-assisted human rights monitoring in the future.