🚀 Aspiring Agentic AI Developer | Gen AI Enthusiast
I’m passionate about building Agentic AI systems and Generative AI applications that solve real-world problems. My focus is on exploring LangGraph, LangChain, and RAG architectures to design autonomous, intelligent agents.
- Agentic AI → Multi-agent systems, autonomy, reasoning with LangGraph
- Generative AI → RAG pipelines, document assistants, and AI-driven recommendations
- LLM Applications → End-to-end apps with Streamlit, LangChain, and vector databases
An AI-powered investment research tool that generates professional financial reports in seconds. It combines market data and news sentiment using a multi-agent LangGraph workflow to deliver clear, actionable investment insights.
A multi-agent newspaper generator built with LangGraph.
This AI agent understands natural language requests to autonomously research topics, perform self-correcting searches, and compose a polished daily newspaper in a Streamlit UI.
A Retrieval-Augmented Generation (RAG) based Anime Recommendation System.
Built with LangChain + Streamlit, it takes your anime preferences in natural language and delivers context-aware recommendations from a curated anime knowledge base.
An AI-powered app for querying and summarizing documents.
Uses LangChain, FAISS, and LLMs to provide a simple yet powerful Streamlit interface for interacting with your documents.
- Advanced multi-agent coordination with LangGraph
- Optimizing RAG pipelines for speed & accuracy
- Building portfolio-ready AI assistants
- Researching Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication
- 💼 Exposure to Appian (Low-code automation)
- ♟️ Hobby: Following chess
- 🌐 LinkedIn: linkedin.com/in/chidambara-raju-g
⭐️ Focused on creating practical Agentic AI solutions that bridge research and real-world applications.