D850 Wildlife Safari: Revolutionizing the Wildlife Tourism Experience with AI

Have you ever tried planning a wildlife safari? If you have, you know that the process can quickly become a logistical nightmare. Between figuring out which gates to book, estimating the costs, and trying to track the territories of specific tigers you want to see, the information is often fragmented and outdated.

We built D850WildlifeSafari.com (https://d850wildlifesafari.com))** to solve this exact problem. Our platform is a comprehensive, AI-powered hub designed for wildlife enthusiasts, photographers, and tourists visiting the Tadoba-Andhari Tiger Reserve (TATR).

🛑 The Problem: Fragmented Wildlife Data Tadoba is one of the most densely populated tiger habitats on earth. It boasts legendary tigers like Chota Matka, Shambhu, Mama and the late Waghdoh. However, for a tourist or a wildlife photographer, getting accurate information is incredibly difficult:

• Which gate should I book to maximize my chances of seeing a specific tiger?
• What is the lineage and history of the tiger I just photographed?
• including permits, gypsies, and guides?

Currently, enthusiasts rely on scattered social media posts, hearsay from local guides, or outdated forums.

🌟 The Solution: D850 Wildlife Safari We envisioned a platform where all this data is centralized, intuitive, and enriched with Artificial Intelligence. D850 Wildlife Safari serves as the ultimate digital companion for your Tadoba journey.

Key Features We Built: 1. Interactive Tiger Biographies & Bloodlines: We created a rich, highly detailed database of Tadoba’s tigers. Users can read deep-dive biographies of legendary tigers, track their lineage (who sired whom), and understand their territorial dynamics. 2. Safari Cost Estimator: A built-in calculator that helps users estimate their travel and safari costs, removing the guesswork from trip planning. 3. Gate & Package Information: Streamlined information on all core and buffer gates (Moharli, Junona, Dewada, Keslaghat, etc.) and available tourism packages.

🤖 Powering Wildlife with GenAI To take our platform to the next level for this hackathon, we integrated Google GenAI using Firebase Genkit.

By leveraging the gemini-2.0-flash model, we are able to introduce smart features into our application. Genkit provided us with an incredibly smooth developer experience, allowing us to seamlessly orchestrate our AI flows directly within our Next.js backend.

• Whether it’s summarizing vast amounts of historical tiger data into bite-sized insights or answering dynamic user queries about Tadoba, Gemini serves as the intelligent brain behind our platform.

🛠️ The Tech Stack We wanted to ensure our platform was blazing fast, beautiful, and highly scalable. Here’s what we used:

• Frontend Framework: Next.js 15 :- For our frontend and routing, we chose Next.js 15 utilizing the App Router. Server-Side Rendering (SSR) & SEO: Wildlife enthusiasts search for specific terms like “Waghdoh tiger lineage” or “Tadoba safari costs.” Next.js allows us to server-side render our heavy data files, ensuring our pages are indexed perfectly by search engines while delivering incredibly fast First Contentful Paint (FCP) times. Component Library: We styled the application using TailwindCSS paired with Radix UI and Framer Motion, allowing us to build accessible, smooth, and highly interactive UI components — from accordion-based itineraries to complex data tables for tiger bloodlines.
• Backend & Database: Firebase (Auth, Firestore, and App Hosting) to manage our data and user authentication seamlessly. Firebase Auth: Handles our user authentication securely and seamlessly. Firebase App Hosting: We utilized Firebase’s new App Hosting designed specifically for Next.js and Angular apps, which made deploying our SSR routes and API endpoints practically zero-config
• AI Integration: The AI Brain: Integrating Gemini via Firebase Genkit. [*@genkit](http://twitter.com/genkit)-ai/googleai* and Firebase Genkit to integrate the Gemini 2.0 Flash model. The crown jewel of our application is the integration of Generative AI to manage and synthesize the vast, complex histories of Tadoba’s tigers. Some of these tigers have 10-year histories involving territory wars, multiple litters, and shifting buffer zones.

Why Genkit? Genkit fundamentally changed how we approached AI integration in this project.

1. TypeScript Native: Genkit allowed us to orchestrate our AI flows natively within our existing TypeScript/Next.js codebase. We didn’t have to spin up a separate Python backend. 2. Developer Experience (DX): Using genkit start, we were able to utilize the Genkit Developer UI locally to test our prompts, inspect traces, and fine-tune the Gemini model’s responses against our local tigers.ts database before pushing to production.

We feed our extensive, deeply nested JSON/TypeScript arrays of tiger data (containing parameters like identifyingMarks, detailedBiography, and lineage) into the Gemini model. By leveraging Gemini 2.0 Flash’s massive context window and lightning-fast inference, the AI can:

• Provide intelligent summaries of a tiger’s history on the fly.
• Answer dynamic queries about territorial disputes (e.g., “How did Chota Matka take over the buffer zone?”).
• Extract specific data points from unstructured biographical text.

Our future roadmap includes: AI-Powered Tiger ID: Allowing users to upload a photo of a tiger and using AI to identify it based on its stripe patterns. Real-time Sightings Map: A community-driven map where verified users can log recent sightings to help others plan their safaris.

• Expansion: Scaling the architecture to support other major national parks in India, like Ranthambore and Bandhavgarh.

We are incredibly proud of what we’ve built, and we can’t wait to see how it empowers the next generation of wildlife explorers. See you in the jungle! 🐅