{"slug": "wildguard-ai", "title": "wildguard ai", "summary": "A developer built WildGuard AI, a multi-agent wildlife identification and safety assistant that lets users upload a wildlife photo and receive coordinated analysis from specialized agents. The system uses Google's open-source Agent Development Kit (ADK) for orchestration and Gemini for model intelligence, separating identification, geographic verification, risk assessment, first aid, and ecological education into independently inspectable agents. It is deployed on GitHub Pages with the source available on GitHub.", "body_md": "*This is a submission for the [Hacktoberfest Weekend Challenge: Build for a Friend](https://dev.to/challenges/hacktoberfest-weekend-2026-10-01)*\n\nI built **WildGuard AI**, an AI-powered multi-agent wildlife identification and safety assistant.\n\nI built it for a friend who enjoys spending time outdoors, where encountering unfamiliar wildlife can quickly become a safety concern. The goal was to create something they could use when they encounter an animal they don't recognize.\n\nA user can upload a wildlife image, and WildGuard AI coordinates multiple specialized agents to:\n\nInstead of relying on one general-purpose agent, WildGuard divides the problem into specialized agents coordinated by an Orchestrator.\n\nLive frontend:\n\n[https://satyakamspc.github.io/Wildguard-AI/](https://satyakamspc.github.io/Wildguard-AI/)\n\nThe project is currently deployed using GitHub Pages.\n\n[WildGuard AI — GitHub Repository](https://github.com/satyakamspc/Wildguard-AI)\n\nWildGuard AI is built around **Google ADK (Agent Development Kit)** as the agent framework, with Gemini providing the model intelligence.\n\nThe system uses a multi-agent architecture consisting of:\n\nThe application is built with:\n\nThe project also uses dedicated Agent Skills for the AI/ML, backend, frontend, and database parts of the application.\n\nWildGuard AI uses the open-source **Google ADK** as the foundation for its multi-agent architecture.\n\nThis was important because wildlife analysis is not a single task. Identification, geographic verification, risk assessment, first aid, and ecological education are different responsibilities that benefit from being separated into independently understandable agents.\n\nUsing an open agent framework allowed me to structure the application around specialized, inspectable components rather than putting the entire workflow inside a single opaque AI prompt.\n\nThe model layer is separated from the agent architecture as well. Gemini currently provides the model intelligence, while ADK handles the agent orchestration and workflow.\n\nThis separation makes the system easier to extend: individual agents can be modified, tested, or replaced without redesigning the entire application.", "url": "https://wpnews.pro/news/wildguard-ai", "canonical_source": "https://dev.to/satyakam_das_891754/wildguard-ai-2lg3", "published_at": "2026-10-04 21:26:20+00:00", "updated_at": "2026-10-04 21:42:16.621070+00:00", "lang": "en", "topics": ["ai-agents", "artificial-intelligence", "generative-ai", "ai-tools", "developer-tools"], "entities": ["WildGuard AI", "Google ADK", "Gemini", "GitHub Pages", "GitHub"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/wildguard-ai", "markdown": "https://wpnews.pro/news/wildguard-ai.md", "text": "https://wpnews.pro/news/wildguard-ai.txt", "jsonld": "https://wpnews.pro/news/wildguard-ai.jsonld"}}