I am Ghazala Arshad, an AI Agent Developer and LLM Engineer based in Hyderabad, Pakistan. I specialize in Retrieval-Augmented Generation (RAG) and multi-agent systems, building low-latency AI agents using frameworks like CrewAI and LangChain. I recently designed and deployed a bilingual (Hindi & English) RAG-based AI agent for a remote project, with sub-second inference latency achieved by integrating Groq Llama3-70B and robust vector stores.
I ranked in the Top 1% globally in Google’s Prompt-to-Agent Engineering Challenges 2025 and published a complete RAG + Multi-Agent system demo on GitHub. I am passionate about delivering efficient, reliable AI solutions for clients worldwide.
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- Built using CrewAI and LangChain frameworks
- Integrated Groq Llama3-70B for sub-second inference latency
- Implemented ChromaDB vector storage with hallucination prevention guardrails
- Multi-agent workflow with planning, reflection, and tool orchestration
Designed and deployed a complete bilingual (Hindi & English) Retrieval-Augmented Generation (RAG) based multi-agent AI system as part of Google’s Prompt-to-Agent Engineering Challenges 2025.
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This project ranked me in the Top 1% globally in the challenge, completed in just 48 hours.
Live Demo & Code: https://www.twine.net/signin
#AI #LLM #RAG #MultiAgent #LangChain #CrewAI #Groq #PromptEngineering #Python
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