CloudFunc AI
Project Overview
CloudFunc AI transforms plain-English cloud requirements into deployable functions using RAG pipelines and templated code generation.
About This Project
CloudFunc AI transforms natural language cloud requirements into deployable serverless code using RAG plus LLM reasoning.
Tech Stack
Team
Mentors
- Nikhil Agarwal
- Lavanya Rathi
- Atharva Parkhi
- Aaryan Yadav
Mentees
- Kowndinya
- Jiya
- Pratham
- Nikitha
- Bhavya
- Mili
- Santosh
- Prashasti
Methodology
The project follows a structured implementation approach that includes Crawl and index cloud documentation, Retrieve context through RAG, Generate structured JSON tasks, Render Python/Node/Go functions via templates, and Run secure sandbox testing. These steps are executed iteratively to validate assumptions, improve performance, and ensure reliable delivery of the final solution.
Expected Outcome
By the end of this project, the team is expected to deliver Faster cloud automation development, Reduced documentation overhead, and Correct trigger and permission scaffolding. Together, these outcomes reflect both technical feasibility and practical value for demos, evaluation, and future scaling.