Nova AI: AI-Powered Code Generation SaaS Using Next.js and LLM

Abstract

In the contemporary software development landscape, transforming natural language ideas into runnable code remains time-consuming and requires significant expertise. Traditional development workflows involve manual coding, repeated iterations, and steep learning curves for non-experts. Recognizing these limitations, this research proposes and presents the development of Nova AI, an AI-powered code generation platform designed as a Software as a Service (SaaS) product that automates the creation of full React applications from natural language prompts. Built on a modern technology stack incorporating Next.js for server-side rendering, React and Tailwind CSS for the frontend, Convex for real-time backend and database operations, and Google’s Gemini LLM for code generation, prompt enhancement, and architecture explanation the platform delivers an intuitive user experience. It offers functionalities such as prompt input with AI-based enhancement, real-time AI-generated React code, live preview and editing via Sandpack, conversational refinement through an in-workspace chat, high-level and low-level design explanations with flowcharts, workspace persistence, token-based usage tracking, and export or deploy options. Deployment on Vercel ensures scalability and accessibility. By integrating cutting-edge large language models with modern web frameworks, this research highlights a viable path toward scalable, efficient, and democratized code generation, addressing gaps in existing AI coding tools while paving the way for future enhancements such as multi-framework support and advanced code analysis.

Introduction

1. Overview

• Software development is essential for innovation but traditional workflows are slow, expertise-dependent, and limit rapid prototyping.

• Large Language Models (LLMs) like Google Gemini enable natural language prompts to generate complete, structured, multi-file applications.

• Nova AI is a SaaS platform designed to turn user prompts into full React applications with iterative refinement, live editing, and architecture explanations.

2. Key Contributions

1. End-to-End Code Generation: Generates runnable React projects from a single prompt.

2. Interactive Chat & Prompt Enhancement: Users can refine projects conversationally for better output.

3. HL/LL Design Explanations: Provides high-level (architecture) and low-level (data flow) summaries with visualizations.

4. Persistent Workspace & Real-Time Editing: Users can track history, edit code live, and preview changes using Sandpack.

5. Deployment & Export: Generated projects can be deployed or exported directly.

3. Motivation

• Developers and non-experts face barriers to translating ideas into code due to time, expertise, and manual workflows.

• Existing AI code tools often lack integrated prompt improvement, persistent workspaces, live preview, and architectural explanations in a single platform.

4. Literature & Existing Tools

5. Architecture & Workflow

1. Client Interface: React components for chat, code editor, workspace, and explain overlay.

2. Authentication: Google OAuth and Convex for identity and token management.

3. API Layer: Next.js API routes call Gemini for code generation, chat, prompt enhancement, and explain features.

4. Database Layer: Convex manages persistent workspaces, messages, and generated files in real-time.

5. AI Layer: Gemini powers code generation, contextual chat, prompt enhancement, and architecture explanations.

Workflow:

• User enters a prompt → workspace created → AI generates chat response + multi-file React code → users refine via chat → code live-previewed in Sandpack → optional HL/LL explanations → export/deploy.

6. Technologies Used

7. Comparison with Traditional & Existing Tools

8. Results

• Nova AI successfully transforms natural language prompts into runnable React applications.

• Supports iterative refinement, live editing, and architectural explanations.

• Limitations: dependent on Gemini API, token limits for free users, currently focuses on React/Sandpack-supported projects.

Conclusion

This project demonstrates that combining a modern web stack (Next.js, React, Convex) with a large language model (Google Gemini) can deliver a functional, user-friendly SaaS platform for generating full React applications from natural language. Nova AI integrates prompt enhancement, multi-turn chat, live code editing and preview, and HL/LL design explanation in a single flow, with workspace persistence and token-based usage. The system is deployable on Vercel and supports both quick demo access and signed-in users with history. Limitations such as API dependency and framework scope can be addressed in future work through multi-framework support, version control, and richer code analysis. In summary, this research shows that a coherent, scalable AI-powered code generation product is feasible and can lower the barrier to turning ideas into runnable applications.

References

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Copyright

Copyright © 2026 Shubham Das, Priyansh Dubey, Adarsh Mishra, Ishaan Pandey, Rajeshri Lanjewar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.