Molta

An AI-powered software modernization assistant that analyze GitHub repositories and generates architecture insights, modernization recommendations, and deployment-ready reports in minutes.

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MOLTA – AI Software Modernization Assistant

Inspiration

Many developers spend a significant amount of time understanding unfamiliar or legacy software before making improvements. Reading documentation, exploring project structures, and identifying technologies manually can be time-consuming.

We wanted to build a simple AI-powered assistant that helps developers quickly understand an existing GitHub repository and receive practical modernization recommendations. That idea led to the creation of MOLTA.

What it does

MOLTA is an AI Software Modernization Assistant that analyzes public GitHub repositories.

Users simply paste a GitHub repository URL, and MOLTA automatically:

  • Retrieves repository metadata
  • Detects frameworks and technologies
  • Reads the project README
  • Generates an AI-powered modernization report
  • Suggests a production-ready Dockerfile
  • Generates Kubernetes deployment manifests
  • Creates a downloadable PDF report

This allows developers to understand software projects much faster and plan modernization efforts with confidence.

How we built it

We developed MOLTA using a modern full-stack architecture.

Frontend

  • React
  • TypeScript
  • Vite
  • Tailwind CSS

Backend

  • FastAPI
  • Python

AI Integration

  • OpenAI Codex CLI

Other Technologies

  • GitHub REST API
  • ReportLab for PDF generation

The frontend communicates with the FastAPI backend, which retrieves repository information from GitHub, performs AI-powered analysis, generates deployment suggestions, and creates downloadable reports.

Challenges we ran into

During development, we faced several challenges:

  • Handling different GitHub repository structures.
  • Detecting technologies from limited repository information.
  • Designing AI prompts that produce consistent modernization recommendations.
  • Integrating frontend, backend, AI analysis, and PDF generation into one workflow.
  • Ensuring the application remained simple while providing meaningful insights.

Each challenge helped us improve both the architecture and user experience of MOLTA.

Accomplishments that we're proud of

We are proud that we successfully built a complete end-to-end workflow that:

  • Analyzes GitHub repositories automatically.
  • Generates AI-based modernization recommendations.
  • Produces Dockerfile suggestions.
  • Generates Kubernetes deployment manifests.
  • Creates downloadable PDF reports.
  • Provides a clean and easy-to-use interface.

Seeing all these components work together as a single application was a major achievement for our team.

What we learned

Building MOLTA helped us gain practical experience with:

  • FastAPI backend development
  • React and TypeScript
  • GitHub REST API integration
  • AI prompt engineering
  • PDF generation using ReportLab
  • Building full-stack AI-powered developer tools

We also learned how important clear architecture and modular design are when developing AI applications.

What's next for MOLTA

We plan to continue improving MOLTA by adding:

  • Multi-language repository support
  • Security vulnerability analysis
  • Code quality scoring
  • CI/CD pipeline recommendations
  • Cloud deployment suggestions
  • Architecture visualization
  • Automated modernization roadmaps
  • Repository health scoring

Our long-term vision is to make MOLTA an intelligent assistant that helps development teams modernize software faster and more efficiently.

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