Real Estate SaaS

Fast Flat Fee is an online real estate platform that allows people to publish private property for sale or rent and manage the selling process on their own or assign it to the chosen agent.

Client's goal

Being a licensed real estate broker the client wanted to ease the procedure of sale or tenancy within the operating region and reduce related expenses for the property sellers and buyers for their benefit as well as to increase customer engagement and minimize the number of routine tasks in one’s own workflow.


Custom real estate marketplace that gives users possibilities and remedies to initiate, manage, discuss and close deals concerning the sale of private real estate property: one/multi-family houses, condos, coOps, villas, lands, etc.

To fully implement the procedure in the digital form and meet customer expectations the platform comes with the following features.

For sellers:

  • Accounts. User profile registration and administration for long-term usage.
  • Listings. Creation, publishing, management, pdf download of multiple ads.
  • Content. Proposition specification including audio and video content.
  • Marketing. Auto property listing on the MLS base and other platforms.
  • Plan. Choice of the deal management type: owner/agent.
  • Promotion. Open-house scheduling like on-demand and notification.
  • Log. All changes to the listings are recorded and can be reviewed anytime.
  • Sales. Offers receiving, comparison, negotiation, and closing.
  • Payments. Transaction processing with multiple paying options.

For buyers:

  • Accounts. User profile registration and administration for long-term usage.
  • Selection. Keyword-based listing search with multiple filters.
  • Calculations. Definition of spent and saved money on a particular deal.
  • Offers. Bid creation, sending, management, negotiation and purchase.

Technical approach

Web solution created using the JS-based tech stack presented below. The project distinguishes usage of Amazon Web Services and namely:

Frontend. For storing its static files, we used configured Bitbucket Pipelines. They build and deploy each commit on the master branch and upload them to AWS S3.

Backend. To ensure seamless performance we run building and deployment scripts that execute the following tasks in the presented order:

1) Creation of a docker image from source files with pre-installed dependencies;

2) Pushing that image on AWS ECS;

3) Configuration of AWS Fargate task to use this repository;

4) Running of this task in the cluster.


The solution that can be considered as one of the most popular examples of real estate automation so far allowed individual property sellers to post over 500 listings and save over $3.6 billion on sale arrangements and fees. The client noticed the simplification of customer acquisition and retention as well as the increase of operational efficiency.


Desktop Screenshots


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