Corruption Complaint Analyzer

Inspiration

Corruption undermines trust in institutions, creates inefficiencies, and limits opportunities for citizens. In Uzbekistan, where many complaints about corruption remain unaddressed, we saw an opportunity to build a solution that enables individuals to report and analyze complaints efficiently. Inspired by the idea of empowering citizens and ensuring transparency, this platform was designed to bridge the gap between the public and actionable legal advice.

What it does

The Corruption Complaint Analyzer allows users to submit complaints in both text and audio formats. The platform processes these complaints using advanced speech-to-text technology (for audio submissions) and analyzes the content using AI tailored to Uzbekistan’s legal system. Users receive clear, professional legal advice and actionable insights on their complaints.

How we built it

The platform was built using: Django for backend functionality, handling user authentication and complaint processing. Custom Uzbek Speech-to-Text Models for audio transcription. OpenAI APIs and LangChain Groq for generating detailed legal analyses. HTML, CSS, and JavaScript for a responsive and intuitive front-end experience. PostgreSQL for secure and scalable data storage. Render for hosting and deployment. The integration of these tools ensures a seamless, user-friendly experience while maintaining robust AI processing capabilities.

Challenges we ran into

Speech-to-Text for Uzbek Language: Building and fine-tuning a model that effectively transcribes Uzbek speech was a significant technical challenge. Legal Insight Generation: Training the AI to provide contextually accurate and actionable legal advice for Uzbekistan’s specific legal framework required extensive testing and adjustment. Secure User Authentication: Ensuring secure handling of sensitive user data while keeping the interface simple was another priority. Audio File Processing: Managing large audio files efficiently without impacting performance posed a challenge.

Accomplishments that we're proud of

Successfully integrating a custom Uzbek speech-to-text model to support local users. Creating a platform that empowers individuals to address corruption complaints with minimal barriers. Developing a responsive and secure platform with a clean user interface. Deploying the solution on a scalable platform for widespread accessibility.

What we learned

Gained expertise in deploying machine learning models for real-world applications. Learned how to handle complex integrations, including AI, cloud hosting, and speech-to-text technologies. Improved understanding of user-centric design, particularly in sensitive applications like legal systems. Realized the importance of balancing innovation with accessibility for users with diverse technological backgrounds.

What's next for Corruption Complaint Analyzer

Multi-Language Support: Expanding the platform to support other regional languages in Uzbekistan. AI Fine-Tuning: Improving the AI's ability to provide even more precise legal analyses tailored to specific types of complaints. Mobile Application: Developing a mobile app for on-the-go submissions and easier access. Data Insights Dashboard: Creating a dashboard for legal authorities to identify trends in corruption complaints and prioritize action. Community Awareness Campaigns: Partnering with organizations to educate the public on using the platform effectively.

Built With

• css
• django
• gemini
• groqapi
• html
• javascript
• langchain
• llm
• postgresql
• python
• render
• rest
• stt