Pawlicy Pal
"How can we reduce barriers for advocates to draft animal-friendly policies in cities?"
Overview
Pawlicy Pal is an AI copilot that helps advocates draft city-specific, legally sound animal-protection ordinances and move them through local processes. Advocates face steep barriers when trying to influence local policy — from lack of legal expertise to difficulty navigating local codes and limited access to successful precedents.
Github repo: https://github.com/Alu018/pawlicy-gpt
Live experience: https://www.pawlicypal.ai/
Role
As the developer for this project, my role involved engineering the full-stack application from start to finish, which includes the front-end interface, back-end API, LLM integration, and database integration. I worked closely with my partner, who worked on UX design and research, following their wireframes, mockups, and design directions. More specifically, I:
- Engineered a full-stack application integrating Google's Gemini LLM with a RAG pipeline for domain-specific retrieval
- Programmed front-end user interface with React and Tailwind CSS
- Developed back-end API endpoints with FastAPI
- Integrated NextAuth with Supabase to handle session management for user authentication and login
- Embedded and stored policy documents in a Pinecone vector database to enable semantic search and retrieval
- Collaborated with UX designer to translate user research to improve usability and engagement
GALLERY
Our lighting talk at the Sentient Futures' AIADM unconference 2025
Chatting with Pawlicy Pal to draft an ordinance
Reviewing the drafted ordinance with Pawlicy Pal
The policy tracker showing the drafted policy.