Velux is a historic Danish company specializing in the production of windows and skylights.
We have collaborated with our client on web projects at European and national level (Velux has more than 2,000 retailers in Italy).
We have designed and developed a management software with microservices architecture for the management of quotations and the creation of installation certificates by dealers and agents.
The software is a B2B solution aimed at authorised companies that directly install Velux products.
.jpg)
We participated in the European project for the Velux Daylight Renders rendering software. It is a platform to allow users to upload photos of their room and the software returns a render of the room with Velux windows. The request is saved and the user, returning to the platform, has the viewing page with all available files (photos and videos).
On the admin side, whoever has to generate the render has a backoffice management panel and a coordinator panel that allows communication between Velux, external suppliers and renders.
Finally, we took care of integrating HubSpot for each step of the Wizard and Salesforce.
A second project in which we took part was the realisation of a platform with a classifier on which files of data providers relating to construction sites and projects are uploaded. These are fed to a black box, the output of which is a series of construction sites and projects reflecting the interests of the user defined in the application development. In addition to data consultation and visualisation, geolocalisation has also been implemented.
For the implementation of the quotation and certificate management system, we adopted amicroservices architecture that allows different applications to communicate via dedicated APIs. Separate applications for quotations, certificates and the dashboard interact efficiently, enabling complete and integrated process management. Furthermore, to ensure a smooth and secure user experience, we implemented Single Sign-On using the CAS (Central Authentication Service) application. For application development, Ruby on Rails, NodeJs and GO frameworks were used, while both PostgreSQL and MongoDB were used for data management, ensuring optimal flexibility and performance according to specific needs.
For the implementation of the tracking system, we used the Django framework for the development of the backend. An artificial intelligence algorithm developed in Python was integrated for advanced data analysis. Process queue management was optimised using RabbitMQ, ensuring efficient and scalable data processing. In addition, integration with Google Maps was integrated to enrich the user experience, allowing users to intuitively visualise geographical information related to tracking activities. The tracking system uses PostgreSQL as the main database for data management, ensuring security and reliability.
