Writing

Technical Articles

Practical GenAI engineering — RAG architecture, agentic systems, Model Context Protocol, local LLM deployment, and the enterprise patterns behind them. Working implementations, not theoretical experiments.

  • Article

QuoteFlow AI: Automated RFQ Processor

QuoteFlow AI is an intelligent automation system that monitors your Gmail inbox for "Request for Quotation" (RFQ) emails, extracts product details using Gemini 1.5 Flash, queries an internal database for pricing, and automatically replies to the customer with a professional qu...

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Retail Intelligence Multi-Agent System

A sophisticated multi-agent workflow built with LangGraph and Google Gemini to perform automated competitive market research. This system simulates a team of specialized retail analysts to help businesses evaluate new store locations. Overview This project uses a directed...

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Procurement MCP Server - Client

A Model Context Protocol (MCP) server implementation for retrieving and managing procurement data including Purchase Requisitions (PR), Purchase Orders (PO), and Goods Receipt Notes (GRN). OverviewThis project implements an open-source standard for connecting AI applications t...

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Synthetic Data Generator using CTGAN

OverviewA production-ready Synthetic Data Generator designed to create realistic, configurable, and scalable synthetic datasets for machine learning, analytics, and testing use cases.Generate realistic synthetic tabular data using CTGAN (Conditional Tabular Generative Advers...

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HR Assistant - RAG Based Application

This project is a Retrieval-Augmented Generation (RAG) application designed to assist HR departments. It allows users to upload HR-related documents (like policy PDFs or employee handbooks) and query them using an LLM (Large Language Model) to get accurate, context-aware answe...

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Showing 6–10 of 10 articles