Technology of Trustami
Our innovative IT infrastructure has its roots in an university research project
and can screen, process and analyze wide areas of the internet on its own.
"We are able to find, aggregate and structure millions of reviews in order to make them available for everyone!"
The idea for Trustami emerged from scientific research at the Technical University of Berlin (TUB). Work related with social media analytics and big data at the chair of information and communication management (IKM), hosted by Prof. Dr. Rüdiger Zarnekow, lead to a first draft of a scalable infrastructure. This infrastructure was extended and tested on the market within a research grant (EXIST) and later became a spin-off and it's own company, the Trustami GmbH. In the early stages Trustami was awarded with the ICT-Innovative Award by the Federal Ministry for Economic Affairs and Energy (BMWi) and is nowadays an established service provider for small and large businesses.
The Trustami system is divided into multiple technology modules. Our Trustami Enterprise Service Bus (TESB) assures a flexible connection of various data sources. For an independent platform integration we use standards like OpenID 2.0 or OAuth. Our data analytics requires a scalable infrastructure which is capable of handling big data including real time processing and pattern matching. For the execution we use data centers in Germany and flexible cloud servers. Other core services are fingerprint based tracking and verification and classification of data with no need of human interaction.
Our Trustami algorithm is self-learning and based on data mining technology. We extended and developed the algorithm especially for recognizing patterns in unstructured content like social media data and identifying trust building characteristics. The basis is a machine learning and AI based system which improves via millions of samples. After finishing the training phase with millions of samples, our algorithm is now able to draw conclusions from unstructured social data from various sources in real time.
The module-based and flexible infrastructure makes it possible to extract data from social media channels, online marketplaces, company websites, price comparison platforms, social networks and many more. We use established protocols for our calculation and benefit from insights from prior and current research projects at the TUB. Since the beginning we rely on current knowledge and state of the art technology in order to provide a consistent analytics model for big data.