Turn Tech into Profit
Gain Profit with Data Science & AI
Improve Up-Selling
Understanding user preferences with semantic recommenders.
Increase Usage Time
Let users love your content with the help of Knowledge Graphs.
Drive Sales
Pefectly answer user search queries with sementic search.

Our Services
SMALL

Potential Analysis
Where does AI provide value to your business.
How you profit from powerful AI systems such as GPT-4.
Understand AI for business leaders.
MEDIUM

Turn Ideas to MVPs
Turn an idea into an evaluated opportunity.
Have customer feedback and business models.
See how the magic works in an examplary implementation.
PREMIUM

AI Services
Develop with us AI services from algorithms to production.
Based on your preference we work in your teams.
Or we manage the development process for you.
Selected References
Knowledge Graph for Semantic Search
Data Product
As Product Owner and Solution Architect, Matthias was responsible for developing an Enterprise Knowledge Graph for a semantic search solution to increase usage time and to enable content exploration.
The Solution
The solution included a custom ontology, numerous machine-learning services, and a complex data ETL pipeline. The multi-cloud environment included GCP, AWS, and Azure. On the data engineering side, core technologies were Terraform, Docker, Kubernetes, Pub/Sub, Microservices, CI/CD pipelines, ArgoCD, and many more.
Key Words
SCRUM • Data Science • Data Engineering • Machine Learning • Knowledge Graph • Ontology • RDF • Kubernetes • Docker • Microservices • Streaming • Semantic Search • Natural Language Processing • Google Cloud • AWS Neptune • GPT-3 • DevOps • Terraform • ArgoCD • Team Leadership • Stakeholder Management • Collaboration • Agile Culture •
Spare Part Prediction Tool
Data Product
As Product Owner, Matthias was responsible for developing an Tool for forecasting the optimal phase-out of products to maximize revenue and to ensure a smooth phase-out.
The Solution
The solution connected the necessary data sources, provided the required information in dashboards to users, and included the forecasting models for predictions. Technically, it was based on SAP HANA, Python, Juypter Notebooks, Tableau, and many more.
Key Words
SCRUM • Data Analytics • Machine Learning • Data Science • SAP HANA • Tableau • AWS • Team Leadership • Collaboration • Product Incubation • Innovation • User Centricity • Project Culture
Energy & Carbon Footprint Optimization Tool
Data Product
As DevOps Engineer and Full-Stack Developer, Noureddine was responsible for building an analytics app that gave recommendations to building operators for how to minimize energy consumption and how to reduce the carbon footprint of buildings.
The Solution
The solution connected the necessary data sources, provided the required information in dashboards to users, and included the forecasting models for predictions. Technically, it was based on SAP HANA, Python, Juypter Notebooks, Tableau, and many more. The solution extracted the required features from ESG data (Environmental, Social, Governance), which came from multiple sources. The solution was build as web app, which visualized the data and displayed the recommended actions for energy reduction. In the background ETL pipelines continuously processes and analyzed the ESG data.
Key Words
SCRUM • Data Analytics • Machine Learning • Data Science • Docker • Jenkins • Django • Python • NodeJS • RabbitMQ • ReactJS • PostgreSQL • PowerBI • Juypter Notebook • MongoDB • Tableau • AWS Databases • AWS EKS • Flutter • Dart • Azure Databases • Azure Pipeline • Azure Data Factory • Azure DevOps • PowerBI