Manage collections on the fly, powered by an AR camera and ML contextualization functionalities.

IAA (Inventory Assistant Application) is a collections management application for Android and iOS tablets. 

It uses Augmented Reality (AR) and Machine Learning (ML) technologies. Resulting in a fully automated inventory inquiring process and creating semantic contextualization in a collection.

Inquire a new asset or check-in an existing one by simply pointing the camera and enhance the metadata by generated summaries.

IAA is built using our Knowledge Recognition API. With this technology as its backbone, it comes with a set of very powerful functions. To name a few: camera-based asset identification; automated inquiry process; and embedded check-in/-out.

The application’s design is intentionally uncluttered with a big emphasis on its AR camera. This camera-first approach makes it very easy to use. Starting either the inquiry of a new asset or detecting an existing one is a matter of pointing the camera.

The app detects whether a recognized asset is within the collection. If it is, it will show the assets’ profile and give the option to add, edit or delete any information. When creating or editing content the app will help by giving suggestions. These suggestions are generated using ML methods.

If an asset is not part of the collection the app will return a list of style-matches from within the collection and give the option to add a new asset to the collection. Newly added assets also will help filling out metadata by generating meaningful texts.


  • Camera-based asset identification, no RFID

    IAA uses advanced technologies (CV and ML) to detect and extract metadata from assets captured with a camera. This solution replaces hardware-heavy solutions such as RFID tagging. Making working with and the management of an inventory faster, more flexible, and sustainable.

  • Semantic and automated inquiry process

    Using our Knowledge Recognition API the application provides enriched metadata for all the assets in a collection. The metadata of an asset will be injected with high-level semantic information such as labels and related Web media. 

    Filling out metadata of an asset is simply scanning the asset and letting the app do the rest. For more information about the specific modules of Knowledge Recognition, see this page.

  • Embedded mobile lending process

    Checking-in and checking-out is a process that has seen much improvement in the past years. However, with the powerful AR camera of IAA, this process becomes even more intuitive and fast.

    Simply scanning the asset which is to be checked-in or checked-out together with a member card with IAA is enough.

  • Search by visual queues

    You can explore your collection using visual queues. Pointing the camera at any detected asset and/or object will return a list of closely matching assets of your collection. It can do this for objects and locations.

  • Search by comparing visual queues

    IAA allows for “comparing” or “adding” multiple visual queues together. Draggin a line between detected assets and/or objects will return a list of closely matching assets based on the joined visual queue. You can search based on a particular book and a flower or a painting and a sculpture for example.

  • Collection specific

    Inventory Assistant needs to be trained on a specific collection or set of collections. This improves performance and removes privacy concerns.


  • June 2020

    Research and concept development

    Starting as an experimental playground for testing KR features we recognized the usefulness of having this app.

  • July 2020

    Development prototype

    Implementing KR API and preparing our own collection of books by joining the bookcases of our team.

  • September 2020

    Testing prototype

    Running tests to see how responsive and easy the prototype is to use.

  • November 2020

    Development IAA beta version (web-based)

    For now resorting to web-based beta version for quicker development and not having issues with different operating systems.

  • April 2021

    Opening IAA beta demo registration form

    Opening forms for people to request a demo of the app.

  • May 2021

    Exclusive release beta version for registered customers

  • July 2021

    Retrieving feedback from the beta release

  • August 2021

    Development IAA version 1.0.0 (iOS and Android)

  • January 2022

    Launch of IAA version 1.0.0


  • Amir Houieh @suslib.com

    Co-founder and developer

  • Martijn de Heer @suslib.com

    Co-founder and designer

  • Ada Popowicz

    Designer, intern