Nevatal

Translator Page
Document (RAG) AI page
Prompt page

Inspiration

As AI continues to grow rapidly, managing multiple APIs and AI tools can get complicated. We wanted to create a single platform AI Functions Hub where users can easily access, experiment with, and build AI-powered features without heavy setup or complex integration.

What it does

Nevatal is an AI functions hub that lets users explore and use various AI capabilities through a unified interface. Simply add your Gemini API key, and you’re ready to go no additional configuration needed.

Prompt-based interactions
Proofreading assistance
Text summarization
Translation services
Content writing and rewriting
AI-powered explanations
Copywriting assistance
Document AI processing
RAG (Retrieval Augmented Generation) chat functionality
Nano Banana Image Generation
Email Builder AI

It provides a smooth full-stack experience, connecting a Django REST Framework backend with Gemini AI and a Vite + React + Tailwind + TypeScript frontend for a fast, clean, and responsive UI.

How we built it

Backend: Built with Django REST Framework to manage API routing, data handling, and integration with Gemini AI.
Frontend: Developed using Vite, React, TailwindCSS, and TypeScript for a modern and efficient user experience.
Containerization: The whole system runs on Docker, making it extremely easy to set up and deploy anywhere.
Integration: Just insert your Gemini API key — everything else is ready to run.

Challenges we ran into

The biggest challenge was designing for user flexibility — figuring out what users actually need from an AI hub and making the setup as simple as possible while still supporting multiple AI functions. We also faced challenges in AI system design, especially in structuring endpoints and managing state between backend and frontend seamlessly.

Accomplishments that we're proud of

Successfully created a working full-stack AI hub that runs smoothly in Docker.
Integrated Gemini API with dynamic endpoints for multiple AI functions.
Built a clean, fast, and type-safe frontend that makes interaction simple and intuitive.
Delivered an easy-to-use setup — just plug in an API key and start using AI.

What we learned

We learned a lot about AI system design, frontend–backend synchronization, and how to simplify developer onboarding. We also gained a deeper understanding of how to structure and scale an AI-driven application efficiently.

What's next for Nevatal

We plan to:

Add more AI use cases and integrations (e.g., text-to-image, embeddings, automation flows).
Introduce user accounts and history storage using Redis and database caching.
Provide custom AI pipelines that users can visually build and connect.
Expand support for multiple AI APIs, not just Gemini.