Snap, collect & place objects.


Dezigner allows users to snap pictures of their favorite pieces of art or furniture, collect them and place them in new spaces or mood boards. The app uses a combination of app embedded Machine Learning models and Augmented Reality features.


Background removal (camera and library)
Object collection
Mood boards
AR placing
Full offline functionality

Launch & Maintenance

Created marketing materials
SEO for AppStore
Analytics and link attributions


iOS development
Machine Learning models development
Multi-device manual testing

Features showcase

Snap, upload, and remove

The users can easily snap or upload from their gallery, pictures of their favorite design items, then they can remove the background and save them for later. The background removal process works in-app, and also offline, without the need for an internet connection.

Edit and export

Artists are creative people that have a lot of ideas and they usually like to try out things, that's why the app allows them to edit the assets, by changing the backgrounds of the collected items and trying out their ideas to find the perfect aesthetic. In addition to this, the assets can be easily exported and used as PNGs in other apps.

Mood boards

Collecting is in our human nature, the app allows its users to collect objects in different mood boards to aid their creative process and see which items go well together. The mood boards can also change colors so it's easy to try out different combinations.

Augmented Reality

Most of us are visualizers, we need to see things with our own eyes so we can better comprehend their entity, and we also need this process to be quick and accessible. So it's always better to visualize objects in their real spaces instead of relying on computer designs and renderings, that's why with Dezigner, any interior designers and artists can see their collection of snaps in real spaces using AR.



2 weeks sprints
Daily standups


1 iOS
1 Machine learning
1 Q&A
1 Designer
1 PO/Scrum master


iOS (Swift)
Tensorflow (Python)


December 2021 - January 2022

Take away and


The main challenge of this project was to offer all the functionalities offline. Also developing in-house Machine Learning models for background removal was fun and a provoking experience. To create an ML model, our developers had to dive deep into the domain of image processing to understand the problem, collect training data, train the model, and make it work on mobile apps.


With this project, we've combined our love for technology with our love for the creative fields. Our designers were cheerful in creating an app that was meant especially for creative people like themselves. On the other hand, our technical team enjoyed the puzzling challenge that this app brought and loved solving a hard problem with cutting-edge technologies.


The main takeaway from this project is that we got to work with Machine Learning models, which can easily identify trends and patterns, is in continuous improvement, has a wide application and can handle multi-dimensional and multi-variety data. All these features open up the world to a new and vast field of possibilities in the realm of mobile applications, reinforcing our belief that we should employ the most advanced and finest available technology to better all parts of our everyday lives.


voicecal — Voice calories counter.


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