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bilaltahseen/README.md

Bilal Tahseen

Generative AI Engineer building agentic systems, LangGraph pipelines, and production-grade RAG at CR8.ai. Freelancing on Upwork/Fiverr. Based in Karachi.

I specialize in the messy middle between research and shipping — multi-agent orchestration, VLM-based design adaptation, MCP servers, and the infra to run it all.

Selected work

  • POS Designer Agent — 5-stage LangGraph pipeline (Analyze → Layout → Generate → Render → QA) for adapting brand assets into retail formats at 300 DPI. Built for Unilever at CR8.ai.
  • konva-mcp — Open-source MCP server connecting LLM agents to a Konva.js canvas via a Node.js bridge.
  • Billing Guidelines Agent — Multi-agent RAG system for law firm invoice compliance. Reduced manual review by 70%+.
  • Interbank Fraud Detection — Cross-bank transaction analysis across 15 institutions, 100M+ AED in monitored volume.

Stack I reach for Python · LangGraph · FastAPI · React · Node.js · vLLM · Puppeteer · PostgreSQL · Pinecone · AWS

Certifications: CKAD · AI Engineer Associate · NED University


bilaltahseen.com · LinkedIn · Medium

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  1. amazon-bedrock-langchain-claude amazon-bedrock-langchain-claude Public

    Python

  2. nestjs-ddd nestjs-ddd Public

    Forked from ecaminero/nestjs-ddd

    TypeScript

  3. document-qa-system document-qa-system Public

    A local Document QA system that allows users to upload PDF documents and ask questions about their content using a Retrieval Augmented Generation (RAG) approach. This project uses a lightweight LLM…

    HTML

  4. Object-Detection-Image-Coordinates-to-Real-World-Coordinate-Conversion Object-Detection-Image-Coordinates-to-Real-World-Coordinate-Conversion Public

    Using tensorflow object detection api and openCV to calculate real world coordinates from top view with fixed height of the camera.

    Python 10 2

  5. retrieval-augmented-qa-system retrieval-augmented-qa-system Public

    A Retrieval-Augmented Generation (RAG) system built with FastAPI, LangChain, and Google Gemini to chat with PDF documents.

    HTML