OpenLitika

OpenLitika was created to make tracking the legislative process accessible to everyone. Currently, understanding complex legislative proposals (such as PECs or PLs) is a major challenge due to dense technical jargon and a lack of organized, user-friendly information. Our solution aggregates open data from the Chamber of Deputies and presents it in an intuitive interface, allowing users to explore and comprehend public policies with ease.

In terms of innovation, we go beyond simple data visualization. We leverage Neo4j to model the Congress as a complex influence graph, applying custom heuristics that estimate the probability of a proposal’s approval. Furthermore, we integrated an AI-driven chatbot using LangChain, which translates technical legislative content and allows users to engage in natural language conversations directly with the PDF documents. This feature enables users to ask specific questions about the text and receive instant, simplified answers, effectively turning static documents into interactive knowledge bases.

Regarding social transformation, our primary goal is to bridge the gap between citizens and politics. By simplifying complex information and providing essential context, we help people track public decisions more consciously, effectively reducing misinformation and fostering a more informed electorate.

In terms of execution, we utilized a modern and robust tech stack: Python with FastAPI for the backend, React and JavaScript for the frontend, and Neo4j as our graph database. The result is a fully functional prototype complete with real-world data, predictive modeling, and an active AI assistant—demonstrating the high potential for scalability and real-world impact of our solution.

Our project followed two distinct phases: a preparatory period focused on frontend design, Neo4j database modeling, and data ingestion, followed by an intensive hackathon build. During the hackathon, we prioritized intelligence and logic, developing the complete backend infrastructure, implementing predictive approval heuristics, and building our AI-powered chatbot, which enables users to engage in natural language conversations directly with legislative PDFs. By bridging this frontend and backend into a cohesive platform, we successfully transformed our foundational work into a functional, AI-driven solution that simplifies complex political data for the public.