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
Let users find what they want to buy with sementic search.
Our Services
SMALL
Potential Analysis
Identify where AI-based services adds profit for you.
Reveal the opportunities how you profit from ChatGPT and GPT-4.
Fully understand the boundaries and the mechanics of AI in our workshops.
MEDIUM
Turn Ideas to MVPs
Turn an opportunity into an evaluated R&D project with us.
Get solid customer feedback and business models with our support.
See how we make the magic work in an examplary implementation.
PREMIUM
AI Services
Develop with us AI services from algorithms to production.
Based on your preference we work embedded in your teams to guide and implement.
Or we manage the whole development process for you as your executive department.
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
