
RescueRoute AI is an autonomous disaster response coordination platform that combines real-time simulation, AI-driven command decisions, and fleet monitoring to optimize emergency response operations. The system features: - Multi-robot fleet simulation with A* pathfinding for obstacle avoidance - Real-time data streaming via Server-Sent Events (SSE) for instant dashboard updates - AI-powered strategic decision-making using Google Gemini to prioritize missions and manage battery constraints - Automatic battery management with intelligent charging station routing - Production-ready architecture with proper state management, CORS security, and structured logging Built during the 48-hour hackathon using FastAPI (backend), Next.js 16 + React 19 (frontend), and Google Gemini AI. The simulation engine manages 5 autonomous robots across a 50×50 grid with obstacles, charging stations, and mission priorities. The architecture is designed to scale from disaster response to warehouse automation and urban logistics scenarios. Tech Stack: FastAPI, Next.js, TypeScript, Tailwind CSS, Google Gemini AI, Docker Compose
15 Feb 2026

One of the biggest challenges in modern research is dealing with information overload. Analysts, researchers, and organizations often need to process vast amounts of unstructured data—ranging from academic papers and PDFs to dynamic web content. Manually filtering, extracting, and validating insights is time-consuming, prone to bias, and difficult to scale. Our project addresses this gap by building a mini AI research lab, a system that combines retrieval, structured extraction, experimentation, and judgment. At its core, we use GPT-5 efficiently as a multi-role reasoning agent rather than just a conversational assistant. For example, GPT-5 powers the Extractor, transforming raw text into structured evidence with minimal noise. The Experimenter module leverages GPT-5 to simulate hypotheses, cross-check facts, and test consistency across different sources. Finally, the Judge role allows GPT-5 to evaluate credibility, logical soundness, and contextual relevance—acting as a safeguard against misinformation. By integrating GPT-5 with hybrid retrieval (FAISS + BM25), we ensure precise context delivery while minimizing token usage. This efficient workflow solves a real-world problem: enabling faster, more reliable, and scalable knowledge discovery.
24 Aug 2025