Freelancers using Pipeliner in Karachi

Freelancers using Pipeliner in KarachiFreelancers using Pipeliner in Karachi

Projects People

Moiz Ahmed Mansoori

Karachi, Pakistan

AI Assistants, RAG Chatbots & Business Workflow Automation

New to Contra

AI Assistants, RAG Chatbots & Business Workflow Automation

Cover image for Built a full-stack Todo app

Built a full-stack Todo app across 5 phases — CLI to cloud-native. Phase 3 adds AI chatbot via LangChain and Groq for natural language task management. Phase 4 containerized with Docker and Kubernetes. Phase 5 deployed on Vercel with Neon PostgreSQL. 4 live deployments.

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Cover image for QueryMind lets you query a

QueryMind lets you query a real database using plain English. Type a question, get an answer — no SQL knowledge needed. Built a production-grade AI agent using LangGraph that converts natural language to SQL, executes it on a real PostgreSQL database with 100,000+ rows, and automatically corrects errors in a retry loop if the query fails. Key features: 7-node LangGraph agent with conditional routing and self-correction pgvector semantic search for intelligent schema retrieval Full observability dashboard with real-time metrics and query history Trace replay — see every step the agent took to answer your question Deployed live: Next.js frontend on Vercel, FastAPI backend on Render Tech: LangGraph · Groq LLaMA 3.3 70B · PostgreSQL · pgvector · FastAPI · Next.js · Tailwind CSS Github: https://github.com/moiz-mansoori/QueryMind-NL2SQL-Agent-System

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Cover image for Built AIRO, a 6-agent ML

Built AIRO, a 6-agent ML automation system using LangGraph and Groq LLaMA 3.3. The system automates the entire ML pipeline from data ingestion to final report generation. Ran 18 experiments achieving RandomForest f1_macro of 0.7329. Features parallel training, MLflow tracking, SHAP explainability, and a dark Streamlit UI with live log streaming.

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Cover image for Built a deployed AI tool

Built a deployed AI tool that lets users upload research papers and query them using natural language. RAG pipeline with vector search retrieves precise context-aware answers. Features PDF parsing, AI summaries, topic modeling, and citation extraction. Live on Render.

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