GSoC 2026 Contributor Introduction – Interest in Agentic RAG (docs-agent)

[Indrasish]

Hello Kubeflow Community,

My name is Indrasish Bhattacharjee, and I am an Applied AI Engineer and a recent graduate in Computer Science (AI/ML) with a strong interest in building production-ready AI systems and generative AI applications. I am excited to participate in Google Summer of Code 2026 with Kubeflow, particularly the project “Agentic RAG on Kubeflow (Expansion of kubeflow/docs-agent)”.

My primary interests lie in LLM systems, retrieval-augmented generation (RAG), and agentic AI architectures. Recently, I built an Agentic Research AI system that converts high-level goals into structured multi-step execution plans using modular agents, along with a cloud-deployed enterprise RAG system for scalable knowledge retrieval across multiple document formats. These systems were implemented using Python, FastAPI, vector databases (FAISS), and deployed on Google Cloud infrastructure.

Currently, I am working with Growthhack Ventures LLP on the core development of a Stock Market Prediction platform, where our team has completed the architecture and security (SOC 2) research phase and is now moving toward the business requirements and system development stage.

I have started exploring the kubeflow/docs-agent repository and plan to run the system locally to better understand its architecture and identify potential areas where I can contribute. I would greatly appreciate any guidance on issues suitable for new contributors or areas where improvements can be made in the RAG pipeline, data ingestion, or agentic capabilities.

I look forward to learning from the Kubeflow community and contributing meaningfully to the project.

Best regards,
Indrasish Bhattacharjee
GitHub: https://github.com/Indrasish7
LinkedIn: https://www.linkedin.com/in/indrasishbhattacharjee/