Our Partners

To satisfy your needs, we work as a team. With our commercial and research partners, we are working to continuously improve our solutions


    



EDSI-Tech

EDSI-Tech is our trusted partner for hosting our applications. They offer a highly secure service. The technical infrastructure is entirely owned and managed by EDSI-Tech in two redundant data-centers in French-speaking Switzerland. Their Content Delivery Network guarantees very fast loading times for any web applications or websites.

Oppidoc

Oppidoc enterprise provides the open source OPPIDUM development framework that we use for a fast and cost effective development of customized web applications. OPPIDUM is one of the first XQuery framework that takes full benefit from native XML databases and turns them into powerful web application engines. The versatile XQuery language allows to deal homogeneously with all the data of an enterprise, whether they are structured or semi-structured. It facilitates the integration with existing services or the development of further services.

MEDIA Research Lab at EPFL

MEDIA (Models and Environments for Document-based Interaction and Authoring) conducted research targeting new models, languages and methods for authoring and reusing semi-structured data in web based environments till end of 2019. Docetis started as a spin-off of the lab, in strong collaboration with Oppidoc, to provide efficient solutions to manage both data-centric and document-centric information through web applications.

Tyrex Research Team at INRIA / CNRS

The Tyrex research group addresses, among other topics, the theoretical foundations of programming languages. The group conducts research on programming language techniques for processing semi-structured data in robust and efficient manners. Their work on automated analysis of XQuery programs is of special interest to us and we collaborate to improve our solutions.

DIVA Research Group at University of Fribourg

DIVA (Document, Image and Video Analysis) Research Group investigates about the behaviour of deep neural networks and optimization of graph edit distance to optimize graph-matching algorithms. One of their application domains relates to document analysis which aims at extracting various type of useful information from raw document images. We are currently collaborating on a project to set up a web-based platform that provides an easy access to publicly available document image analysis methods. The goal is to provide solutions to private or public organizations that need to extract valuable information from scanned documents.