boost collaboration
we help enterprises.
save costs and time


Our solutions are based on Semantic Web technologies. Among others, we aim at using light-weight technologies and standards such as RDFa, SIOC and FOAF. This makes our solutions easy-to-integrate with any third-party applications. Moreover, using such standards enables us to get new structured data from various sources (e.g., Sindice, and also to make our similarity-measurement algorithms more accurate.


We developed recommendation algorithms to eliminate "information overload" and "information shortage" within enterprises (on top of novel techniques). We use data mining and machine learning methods to infer new knowledge from existing knowledge and to boost our recommendation algorithms.


Nowadays, most enterprises use various sort of social media, such as blogs and micro-blogs (e.g. Twitter). Social Network Analysis (SNA) has lots of potential. We use various sort of analyses, mainly within professional online shared workspaces, in order to find out any latent connections among people. Later, we use such links to infer new knowledge and to discover collaboration opportunities among personnel.


We benefit from Natural Language Processing (NLP) techniques to boost our algorithms. Using NLP, we automated the process of analyzing documents, reports, deliverables, etc. in order to infer any latent knowledge automatically.