CrewAI multi-agent router system with local LLM integration (Ollama + Llama 3.1). Intelligent intent classification with specialized file and math agents.

A Multi-Agent RAG system that acts as my digital twin. Built with CrewAI and LangChain to analyze my CV and answer professional inquiries using my own voice and experience.

CrewAI-MultiAgent is my learning journey through the CrewAI Multi-Agent course. I'll be updating this repo with insights, code, and projects as I explore LLM-based agents, task planning, collaboration, and real-world applications. Follow along for hands-on experiments and implementations! 🚀

A multi-agent financial analysis pipeline built with the crewai framework during my internship at Netsol. The system coordinates specialized agents for KPI insights, financial audits (P&L, cash flow, balance sheet), and diagnostic synthesis, with support for flow-based visualization.

A comprehensive repository dedicated to mastering and implementing state-of-the-art LLM orchestration and Agentic workflows. It serves as a living documentation of my journey through the GenAI landscape—moving from basic RAG pipelines to complex, multi-agent systems using LangGraph and CrewAI, finalized with robust LLMOps practices and cloud deploy

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My personal multi-agent FPL assistant using CrewAI

This repository documents my learning journey with CrewAI. It contains various agent implementations, experiments, and practical examples that I build while exploring multi-agent systems and AI agent orchestration.

📚 A repository documenting my journey in learning CrewAI—exploring multi-agent systems, workflows, and AI collaboration. Includes code examples, experiments, and progress notes.

Multi-Agent Systems Projects This repository showcases various Multi-Agent Systems developed as part of my learning journey in the "Multi AI Agent Systems with crewAI" course by DeepLearning.AI. These projects highlight the power of leveraging multiple AI agents working collaboratively to solve complex problems efficiently and dynamically.

CrewAI Learning Journey documents my hands-on experience building multi-agent AI systems using CrewAI and LLMs. It explores agent roles, task orchestration, tool integration, and real-world workflows like research automation, content generation, and AI-driven decision-making using Python and modern AI frameworks.

CrewAI Learning Journey documents my hands-on experience building multi-agent AI systems using CrewAI and LLMs. It explores agent roles, task orchestration, tool integration, and real-world workflows like research automation, content generation, and AI-driven decision-making using Python and modern AI frameworks.

Multi-Agentic app using CrewAI that parses software specification documents to generate user stories, test cases, code, and automated tests. Built during my summer internship at Accenture

🚀 Introducing AI-Powered Multi-Agent Workflows! Excited to unveil my latest CrewAI-powered automation system! 🚀 This project optimizes LLM workflows, enhances retrieval efficiency, and automates research processes—boosting AI-driven decision-making and response generation. #AI #CrewAI #MachineLearning #Python #Automation #LLM

This repo contains the all the execersices from Multi AI Agent Systems with crewAI (DeepLearningAI) course. It might also contain similar developments with my tweaks and trials either temporally or permanently.

This repository contains my ongoing learnings and hands-on implementations from the Agentic AI 2.0 course taught by Krish Naik. The course covers end-to-end agentic AI development including LangChain, LangGraph, CrewAI, RAG systems, multi-agent collaboration, automation, deployment with Docker & AWS, and monitoring using LangSmith & Opik.