"Working with SIDESTREAM is really fun. Ideas are implemented quickly, communication is straightforward and the modern development approach ensures high quality and speed. With Proprate, we have jointly developed an innovative product and I look forward to further collaboration."
ACCENTRO Real Estate AG is the market leader in residential privatization in Germany. A large part of the customer base is made up of private investors who purchase real estate from ACCENTRO as an investment. Such investments are linked to important parameters. For example, properties are compared on the basis of location, market price, potential return and price development. Excel spreadsheets are often used for this purpose, but their maintenance and creation is laborious and error-prone. For this reason, there was a need for a more efficient software solution to this problem. A clear real estate comparison site for private investors was to be created. In cooperation with the agency Cheil, we put the requirements into an intuitive web application called “PropRate”.
The Sidestream Approach
Cheil first developed a concept for this. For us it meant:
Make the developed concept and user interface work as a web application. To do this, we first evaluated the feasibility. First, we had to identify basic features and functions in order to develop a first product (MVP) in coordination with our project partner. It was important to combine the implementation of the features with the user experience (UX) developed by Cheil in a meaningful way. This guaranteed a fast implementation with a focus on quality and also enables the use of state-of-the-art software technologies in the future.
The implementation: Focus on code quality and UX
Based on the design developed by Cheil, we delivered the MVP in five sprints. Within these five weeks, we delivered the entire software architecture, developed the core features and already conducted test runs. The special feature here was that we worked particularly closely with our project partner on this project. The daily exchange with Cheil throughout the development enabled a direct culture of cooperation between UX and development specialists.
The product: efficiency and user-friendliness
Efficiency and user-friendliness are at the core of this project: “PropRate” combines both better data processing and a clear and intuitive user interface. Instead of tedious, manual work, the user is offered an automated solution. For example, the scraping of web pages enables the pre-filling of data such as the real estate purchase price. With just a few clicks, “PropRate” evaluates relevant properties and clearly displays the most important comparative values. Thus, nothing stands in the way of potential investments. In the future, the planned AI will completely take over the comparison process and thus find the right property without any effort on the part of the user.
Technology Deep Dive
The challenge in implementing this project was to develop a stable, scalable application with a good look and feel, and to do so in a lean way and in a short time. Our solution: the AWS Amplify Stack. Equipped with this set of tools and services, we got off to a fast start without sacrificing quality. The web application is a modern mix of GraphQL, Nuxt and VueJS. The complete API is generated automatically. All we had to do was write a GraphQL schema. Everything else happens on its own. Because AWS Amplify generates an AWS AppSync application including access rights and authentication off-the-shelf. It also pulls up a DynamoDB in parallel.
The deployment including CI/CD pipeline is also virtually automatic. Each commit in the master is automatically built, tested and then deployed. This composition enables a high development speed. Meanwhile, Tailwind - our favorite CSS library - in interaction with VueJS ensures perfect modularity and flexible reusability of the individual components. It also guarantees one hundred percent flexibility and individuality in look & feel. This foundation opens up a fast and easy implementation of future features. One of them will be the evaluation by means of Machine Learning!