FireForm: An Open Source “Report Once, File Everywhere” System for First Responders

FireForm aims to solve a critical problem faced by first responders: the need to repeatedly document the same incident across multiple agency-specific forms, leading to significant time loss and increased chances of errors. This project focuses on transforming FireForm from a prototype into a production-ready system that enables a “report once, file everywhere” workflow. My approach is to strengthen the core AI-driven pipeline by integrating Whisper-based voice transcription, improving structured data extraction using local LLMs (via Ollama), and introducing robust validation and retry mechanisms using Pydantic. Additionally, I will design a flexible YAML-based template system that supports multiple agency-specific PDF forms without requiring code changes. The project will also implement structured error handling, comprehensive testing, and CI/CD workflows to ensure reliability in real-world deployments. By the end of the program, FireForm will be a scalable, modular, and dependable system capable of converting natural language incident reports into accurate, multi-agency documentation, significantly reducing administrative overhead for first responders and improving operational efficiency.