01/03/2026
๐๐๐๐๐๐ข๐ง๐ข๐ง๐ ๐๐ซ๐จ๐ฉ๐๐๐๐ก ๐ฐ๐ข๐ญ๐ก ๐๐: ๐๐ก๐ซ๐ข๐ฅ๐ฅ๐๐ ๐ญ๐จ ๐ฎ๐ง๐ฏ๐๐ข๐ฅ ๐ฆ๐ฒ ๐ฅ๐๐ญ๐๐ฌ๐ญ ๐๐ฎ๐ฅ๐ฅ-๐ฌ๐ญ๐๐๐ค ๐๐ฃ๐๐ง๐ ๐จ ๐ฉ๐ซ๐จ๐ฃ๐๐๐ญ, ๐๐ข๐ซ๐๐ฉ๐จ๐๐๐๐ฌ๐ญ!
I wanted to build more than just a real estate listing site. I wanted to engineer a secure, intelligent ecosystem that actively works for its users. By leveraging a custom dataset of over 32,000 property records, I integrated advanced Machine Learning architectures and strict security protocols to completely eliminate brokers and create total market transparency.
Here is a look under the hood at the engineering behind the NirapodNest system:
๐๐ก๐ ๐๐๐๐ก๐ข๐ง๐ ๐๐๐๐ซ๐ง๐ข๐ง๐ ๐๐ง๐ ๐ข๐ง๐ (๐๐ซ๐๐ข๐ง๐๐ ๐จ๐ง ๐๐๐ค+ ๐๐๐๐จ๐ซ๐๐ฌ)
๐๐ซ๐ข๐๐ ๐๐ฌ๐ญ๐ข๐ฆ๐๐ญ๐จ๐ซ & ๐๐๐ซ๐ค๐๐ญ ๐๐๐ซ๐ข๐๐ง๐๐ (๐๐๐๐จ๐จ๐ฌ๐ญ ๐๐๐ ๐ซ๐๐ฌ๐ฌ๐จ๐ซ): A custom XGBoost model analyzes live market data to instantly calculate an accurate predicted asking price for sales or rentals. To empower users, the system automatically compares the owner's listed price against the AI prediction, displaying the exact market variance and highlighting any markup in real-time.
๐๐๐ญ๐ฎ๐ซ๐๐ฅ ๐๐๐ง๐ ๐ฎ๐๐ ๐ ๐๐๐๐ซ๐๐ก (๐ฌ๐ฉ๐๐๐ฒ ๐๐๐ + ๐๐๐ ๐๐ฑ): To make the platform hyper-accessible, I implemented a smart text-based search. Using spaCy for NLP combined with custom Regex parsing, users can simply type their requirements in plain English, and the engine instantly translates their natural text into complex database queries.
๐๐ฎ๐ฉ๐ฉ๐จ๐ซ๐ญ ๐๐ก๐๐ญ๐๐จ๐ญ (๐๐๐ ๐ฏ๐ข๐ ๐
๐๐๐๐): Built a Retrieval-Augmented Generation (RAG) pipeline using LangChain and a FAISS vector database to answer complex user FAQs instantly based on semantic meaning, bypassing the limitations of basic keyword matching.
๐๐๐ข๐ ๐ก๐๐จ๐ซ๐ก๐จ๐จ๐ ๐๐ง๐ฌ๐ข๐ ๐ก๐ญ๐ฌ (๐๐๐จ๐ฌ๐ฉ๐๐ญ๐ข๐๐ฅ ๐๐จ๐ ๐ข๐ ๐๐ง๐ ๐ข๐ง๐): A custom geospatial engine that goes beyond standard amenities. It generates comprehensive neighborhood insights and assigns a custom livability rating based on specific property details and location data, helping users understand the true vibe of an area.
๐๐ฆ๐๐ซ๐ญ ๐๐ฎ๐ญ๐จ-๐๐๐ง๐๐ซ๐๐ญ๐จ๐ซ: An NLP tool that cross-references a propertyโs specs and location to automatically write highly professional, context-aware property descriptions for owners.
๐๐๐ซ๐ค๐๐ญ ๐๐๐๐๐ซ ๐๐ฅ๐๐ซ๐ญ๐ฌ (๐-๐๐๐๐ซ๐๐ฌ๐ญ ๐๐๐ข๐ ๐ก๐๐จ๐ซ๐ฌ): Users don't have to endlessly scroll. I engineered a highly customizable Market Radar using a K-Nearest Neighbors (KNN) algorithm that constantly scans the database for properties matching a user's exact multi-dimensional criteria. It pushes alerts via the in-app notification bar and email based on user preference: Instant, Weekly, or at a Daily User-Defined Time.
๐๐ฎ๐ฅ๐ญ๐ข-๐๐๐ฒ๐๐ซ ๐๐๐๐ฎ๐ซ๐ข๐ญ๐ฒ & ๐๐๐ซ๐จ-๐๐จ๐ฅ๐๐ซ๐๐ง๐๐ ๐
๐ซ๐๐ฎ๐ ๐๐๐ญ๐๐๐ญ๐ข๐จ๐ง: Security is non-negotiable. I implemented a strict, multi-layer verification process during account creation. If a new user attempts to register using the sensitive details (like NID or a claimed property address) of an already verified user, the system's anti-fraud engine catches it and executes an immediate, automatic ban on the fraudulent account.
๐๐๐๐ฅ-๐๐ข๐ฆ๐ ๐๐จ๐ฆ๐ฆ๐ฎ๐ง๐ข๐๐๐ญ๐ข๐จ๐ง: To completely remove the middleman, I built a seamless, real-time messaging architecture allowing verified buyers and renters to chat directly with property owners.
๐๐จ๐ซ๐ ๐๐ญ๐๐๐ค: Python, Django, PostgreSQL, XGBoost, Scikit-Learn, spaCy, LangChain, FAISS, React JS.
Building NirapodNest pushed me to bridge the gap between heavy AI data processing, strict backend security, and a flawless user experience.
Check out the video below to see the AI and security features in action! Iโd love to hear your thoughts or feedback in the comments.
