SearchLand

About project

Searchland is a B2B off-market land sourcing platform that offers comprehensive data on property and land, empowering businesses to efficiently identify and acquire valuable off-market opportunities. By providing accurate, real-time insights, Searchland streamlines the land sourcing process for investors, developers, and real estate professionals.

Duration

04.2023 – 04.2024

teCHNOLOGIES

Typescript, React.js, Next.js, Node.js, Nest.js, MUI, GraphQL (Apollo), Open AI, Storybook, Kubernetes, Puppeteer, ArcGIS

Business solutions

modular and Scalable Architecture:
Leveraged the Nx monorepo structure and adopted a microservices architecture with Node.js and Nest.js to ensure a highly modular and scalable platform. This allows for easier maintenance, future upgrades, and more efficient handling of business requirements as the platform grows.
AI-Driven Insights for Data Processing:
Integrated GPT models from OpenAI to automate data analysis and generate actionable insights, improving the accuracy and speed of decision-making for users. This AI-powered feature adds value by enhancing the ability to process large volumes of property and land data.
real-time Data Gathering with Automation:
Deployed Puppeteer for automated web scraping, allowing the platform to gather real-time data from various sources and update the system with the latest property information. This ensures that users always have access to current and relevant data for land sourcing and decision-making.
geographic Data Analysis and Visualization:
Integrated ArcGIS to provide geographic data analysis and visualization, enabling users to easily view and interpret land and property data on interactive maps. This allows businesses to make more informed decisions based on geographical insights, such as location advantages or zoning data.

deveLOPMENT PROCESS

architecture Design and Codebase Structure:
Utilized the Nx monorepo structure to create a unified, modular, and scalable codebase. Adopted a microservices architecture for backend services with Node.js and Nest.js, ensuring that each module could be developed and maintained independently while ensuring smooth communication between services.
AI Integration for Data Analysis:
Integrated OpenAI’s GPT models to process and analyze large datasets pulled by the Chrome extension. This AI-driven data processing aids users in deriving advanced insights from raw property and land data, optimizing decision-making and enabling faster and more accurate analyses.
automated Data Collection with Web Scraping:
Implemented Puppeteer for automated web scraping, enabling real-time extraction of data from diverse online sources. This feature ensures the platform stays up-to-date with fresh, relevant property and land data, giving users a competitive edge in sourcing off-market opportunities.
geographic Data Integration and Mapping:
Worked with ArcGIS to provide geographical data analysis, enabling users to visualize land data through interactive web maps. This integration also allowed for data extraction and uploads to the ArcGIS server, enhancing the platform’s ability to support location-based decision-making and analysis.

Roadmap

Modular Architecture and Microservices Setup

04.2023 - 07.2023

Implement Nx monorepo structure for a modular, scalable codebase.
Adopt microservices architecture using Node.js and Nest.js for backend services, ensuring maintainability and scalability.
Set up initial backend and frontend services, ensuring independent module management and communication.

AI Integration for Data Processing and Insights

06.2023 - 09.2023

Integrate GPT models from OpenAI to process and analyze land and property data gathered through the Chrome extension.
Implement AI-driven features to provide users with advanced insights, enhancing data analysis and decision-making.
Develop UI components for presenting AI insights to users in an intuitive manner.

Automated Data Gathering and Geographic Analysis

09.2023 - 01.2024

Deploy Puppeteer for real-time web scraping to gather property and land data from various online sources.
Integrate ArcGIS for geographic data analysis and visualization, enabling users to view and interpret data on interactive maps.
Implement extraction and upload functionality for geographic data to ArcGIS servers.

Optimization, Testing, and Finalization

01.2024 - 04.2024

Conduct optimization of the platform to improve performance, scalability, and reliability.
Test and refine AI-driven features, geographic data tools, and web scraping functionalities to ensure seamless operation.
Finalize deployment, ensure data accuracy, and prepare the platform for full-scale release.

Main Functionality

Modular and Scalable Architecture:

The platform is built on a modular and scalable codebase using the Nx monorepo structure, enabling easy maintenance, faster updates, and smoother scalability as new features are added.

AI-Driven Data Processing and Insights:

GPT models from OpenAI are integrated to process and analyze data from the Chrome extension. This AI-powered functionality provides users with actionable, real-time insights and advanced data analysis, improving decision-making.

Automated Web Scraping for Real-Time Data:

Puppeteer is used for automated web scraping, gathering real-time property and land data from various online sources. This ensures that the platform provides users with up-to-date, relevant information for off-market land sourcing.

Geographic Data Visualization and Analysis:

ArcGIS integration enables geographic data analysis and visualization, allowing users to view and interpret property and land data on interactive maps. This enhances decision-making by offering spatial insights such as location advantages, zoning information, and land availability.

Contact Us

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