m
muqaddas_b7

Muqaddas

@muqaddas_b7

AI Engineer Expert in LangChain Groq RAG Pipelines and FastAPI Development

Pakistan
English, Urdu
About me
AI Engineer specializing in RAG pipelines, LLM integration, and full-stack AI applications using LangChain, Groq, and FastAPI. Projects: Vocaro (AI Meeting Intelligence Platform), MediAssist (healthcare RAG chatbot), NexVisa (visa information system for 192+ countries). I deliver clean, deployable code with React frontends and FastAPI backends. Let's build something smart together.... Read more

Skills

m
muqaddas_b7
Muqaddas
Offline • 
Average response time: 1 hour

See my services

AI Chatbot Development
I will build a custom ai chatbot with rag pipeline and fastapi
From$30 / projectMore details
AI Integrations
I will build a fastapi backend with llm integration
From$90 / projectMore details

Portfolio

Work experience

Self_Employed

Self Employed

Self-employed • 5 mos

AI Engineer

Mar 2026 - Jun 2026 • 3 mos

Built and deployed two full-stack AI applications as independent projects. MediAssist is a healthcare RAG chatbot developed using LangChain, Groq, and FastAPI. It answers medical queries by retrieving relevant information from a knowledge base using retrieval augmented generation, providing accurate and context-aware responses. NexVisa is an automated visa information system covering 192 plus countries. Built with LLM integration and FastAPI backend, it provides users with up-to-date visa requirements and application guidance through a conversational AI interface. Both applications are fully deployed, documented, and available on GitHub.

AI Engineer and Full Stack Developer

Jan 2026 - Mar 2026 • 2 mos

Designed and deployed Vocaro, a full-stack AI Meeting Intelligence Platform that automatically transcribes and summarizes meetings. Built a FastAPI backend integrated with Groq LLaMA 3 for smart summarization and Groq Whisper API for real-time audio transcription. Developed a clean React TypeScript frontend deployed on Vercel with the backend hosted on Hugging Face Spaces. Handled end-to-end development including API design, LLM integration, error handling, Docker configuration, and production deployment.