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CivicLens

Actionable civic insights through human–AI collaboration
Built at Polderr Hackathon · 9 November 2025

Demo CivicLens


Team


Problem

Municipalities and civic actors often struggle to:

  • Keep a high-level overview of local issues
  • Track short-term and long-term trends
  • Detect misinformation early
  • Extract actionable insights from fragmented online discussions

Relevant information exists but is scattered across forums, local news, and discussions, making synthesis slow and manual.


Solution

CivicLens aggregates public online sources and turns them into structured, actionable civic intelligence, combining AI analysis with human collaboration.

Key idea: Humans and AI work together on real civic problems, using shared context and verified sources.


Core Features

  • Local search engine for news and discussions (USP)
  • AI-assisted summarization of events, topics, and discussions
  • Human–AI collaboration via topic-based forums (USP)
  • Trends overview (short & long term)
  • Misinformation detection and flagging
  • Ready-to-send reports generated from discussions
  • Supports multiple input formats: forums, articles, posts

Topics & Events diagram


Sources

Main: Online forums, local news feeds
Considered: Social media, additional online forums

Assumption: Public websites can be legally parsed as long as no personal data (e.g., usernames) is stored.


Getting started

pip install -r requirements.txt
brew install ffmpeg
ollama pull qwen3-vl:4b-instruct
python -m api.main
cd munincipalitator3000
npm run dev

Re-generate the json with the data

python main_generate.py

Models were using

  • locally hosted via ollama : qwen3-vl:4b-instruct for image to text for eval newspapers etc...
  • azerion hosted
    • elevenlabs-scribe for speech to text
    • gemini-embedding-001 for embeddings
    • mistral-large-2407-v1:0 for nlp decision making

Showcase via sample.png and sample.mp4

AI ChatBot

To activate, use: Hey, PolderrAI

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