JustiFY -Justice Simplified For You
Inspiration
In India, millions of people, especially those from rural and underprivileged communities struggle to access legal information and affordable legal aid. The complexity of legal language and lack of awareness about rights make the justice system feel distant. I am inspired to bridge this gap with technology, making law more approachable and democratizing access to justice using AI.
What it does
1.Understands user’s legal problem in native language (voice input). 2.Searches Indian legal databases for relevant laws. 3.Explains rights in plain language. 4.Auto-generates legal document drafts.
How we built it
I used Natural Language Processing (NLP) to process user queries in plain English/Hindi. Built a legal chatbot interface to provide instant responses on legal rights, processes, and government schemes. Integrated a case law and rights database (public domain datasets). Added a voice interaction layer for accessibility in low-literacy communities. Deployed using Flask + FastAPI backend, and experimented with LangChain for retrieval-based Q&A.
Challenges we ran into
Finding and cleaning open-source legal datasets. Translating complex legal terms into easy-to-understand language. Ensuring responses are accurate, unbiased, and safe (since legal advice carries responsibility). Building a prototype with limited resources while keeping the solution scalable.
Accomplishments that we're proud of
Prototype voice-to-legal draft pipeline, multilingual support.
What we learned
How to train AI models to understand legal domain-specific queries. The importance of user experience in social impact projects (clear UI, simple language, accessibility). Legal-tech requires balancing accuracy with clarity—users should not feel overwhelmed. Collaboration between technology and legal research is crucial.
What's next for JustiFY
Scale to more languages, mobile app version.
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