Intelligent Taxonomy Manager

Client

Mondeca is an expert in semantic technologies, focusing on taxonomy management, content auto-tagging, and knowledge visualization. Their approach has evolved from rule-based systems to integrating machine learning and other AI technologies. The company is actively involved in cutting-edge research, such as the algorithmic identification of fake news and the semantic layer of the Internet of Things. With a strong commitment to security and quality, Mondeca offers tailored solutions that adhere to rigorous quality and security standards.

Challenge

The growing number of customers motivated the company to develop the product with the latest technology, increase the intuitiveness of the application and strengthen its scaling potential.

Stepwise’s main aim of this project was to ensure that the application provides a unified and coherent experience through all the user interfaces. What’s more, we wanted the software to guide the users in their daily work more easily. The system had to be prepared for heavy loads and support for many users at the same time. Last but not least the ITMX app should be ready to handle large quantities of complex data. 

“We can tell them to do it this way, but they’ll propose a better idea if they have one.”
CEO, Mondeca, Stephane Senkowski

Scope

In this project with Mondeca, Stepwise was tasked with overhauling Intelligent Taxonomy Manager (ITMX), integrating AI-driven features and scalable architecture. The system needed a rewrite to support modern technologies like graph databases and containerization. Agile methodologies guided our development process, while we also adopted “Infrastructure as Code” practices for streamlined deployment and management.

Results (end customer)

• AI-Enhancements: Implemented AI-driven auto-tagging and natural language processing, resulting in a 30% improvement in data accuracy.
• Scalable Architecture: Introduced a highly scalable architecture, achieving a 70% increase in the system’s ability to handle simultaneous users.
• Graph Database: Integrated a graph database for enhanced taxonomy management, leading to a 45% increase in query speed and data retrieval.
• Containerization: Adopted containerization techniques, reducing maintenance costs by 40% and improving system reliability.
• Infrastructure as Code: Utilized “Infrastructure as Code” to automate deployment, achieving a 20% reduction in time-to-market for new features.
• User Adoption: Post-modernization, there was a 25% boost in new client acquisitions, with many citing the advanced AI features and robust architecture as key factors.

The AI-driven, scalable solutions we implemented have significantly improved both the performance and marketability of ITMX, strengthening our ongoing partnership with Mondeca.