Guides users to buying a desired property in a certain timeframe and informs how much to save each month.
Provides projections on the maximum loan size, mortgage interest rate, and monthly payments based on a user’s income, location, and savings.
Recommends savings accounts a user can benefit to save as much as possible for a deposit to get a property sooner.
App integrates with banks, real estate companies, credit reporting agencies, and open banking solutions.
Enables the necessary isolation between the application server and business processes.
TypeScript improves readability, speeds up development, and makes the system more stable.
A Node.js-based cluster module allows the app to use the full power of CPU.
Functional, integration, confirmation, and regression testing were performed in order to gain a cloud perimeter and IT infrastructure security assessment.
Grey-box penetration testing was used to detect possible security defects missed during manual examination and automated source code scanning.
Prevents data leaks and backdoors by automatically detecting and locating security flaws in the source code.
PROPERTY PURCHASES PLANNED