CivicAI – Intelligent Governance Co-Pilot

Inspiration

Traditional grievance systems are slow, manual, and lack transparency. Citizens often don’t know the status of their complaints, and administrators struggle with scattered data.

We wanted to build a smart, AI-powered governance assistant that transforms complaints into structured insights and enables faster, transparent, and citizen-centric decision-making.

What it does

CivicAI converts unstructured complaints (text or voice) into actionable intelligence.

It:

Classifies issues (Roads, Water, Electricity, Healthcare)

Extracts location and urgency

Assigns smart priority

Routes tickets automatically

Generates dashboards & heatmaps

Priority scoring formula: Priority=α(Urgency)+β(Sentiment)+γ(Frequency)

How we built it

Frontend: React

Backend: FastAPI (Python)

AI Layer: LLM API for classification + entity extraction

Database: Firebase / MongoDB

Visualization: Chart libraries + geo heatmaps

Example backend logic:

def classify_complaint(text): response = llm_api(text) return response["category"], response["location"] Challenges we ran into

Handling noisy and incomplete text

Improving AI classification accuracy

Managing API limits

Building real-time dashboards within hackathon time

Accomplishments that we're proud of

We built an end-to-end AI pipeline from complaint submission to automated routing and analytics. The live AI extraction demo was a major highlight.

What we learned

Practical LLM integration

Prompt engineering

AI workflow design

Team collaboration under time pressure

What's next for CivicAI – Intelligent Governance Co-Pilot

Multilingual voice support

Predictive issue detection

Mobile app integration

Advanced AI policy recommendations

Learn more about civic innovation at UN E-Government Knowledgebase .

Built With

• fastapi
• firebase
• javascript
• llm
• llm-api
• python
• react
• rest-apis