Applied Machine Learning & Artificial Intelligence

Transfer of cutting-edge research to individual industry problems

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MotionBoxx - GDPR-conform Areal Monitoring

The affordable and rapidly deployable counting solution

Traffic management, urban planning, and environmental protection require current location specific and object specific motion data.

Distinguishing between different objects and at the same time preserving privacy and ensuring affordability are the key challenges when counting objects in public spaces.

MotionBoxx’s AI instantly counts task specific objects on device and sends the non-personal data in real-time to the monitoring dashboard.

Our Solution

MotionBoxx’s camera provides 100% coverage on a predefined area. Video Data is processed instandly on device by specialized Deep Learning algorithms and hardware.

No video or other personal data is stored. The extracted motion data is GDPR-conform and can be freely shared between projects and with external clients.

The lightweight motion data is transferred to the monitoring dashboard in real time, even over low bandwidth (GSM) connnections. Data can be easiliy exported.

Digitalization & Automation

Sustainable digitalization and process automation using Artificial Intelligence (AI) and Machine Learning (ML) methods.

Data Digitization

Our machine learning models intelligently extract & categorize information from satellite images, health records, PDFs, location data, identity cards and more.
We use state-of-the art techniques in image recognition, natural language processing and signal processing to extract & categorize information.

Process Automation

We automate processes with ML that otherwise require human supervision.
We work on applications ranging from predictive maintenance in manufacturing to underwriting insurance risks.
We transfer existing processes into formal specifications that can be solved by ML-methods.

Prototyping

We believe that ML-solutions are best developed with iterative end-to-end prototypes.
This allows us to ensure that data quality & availability and model complexity reflect the business objective.
We develop prototypes that fulfill all critical requirements of the production system.

Our experienced team members worked in digitalization & research projects with:
Bayer Technology Services - Google Research - Victorinox - Swiss Re - IFH Cologne

Custom Machine Learning Solutions

Transferring academic & industry machine learning research into powerful solutions requires a combination of deep technical understanding, state-of-the-art tools, and the right development approach.

Artificial Intelligence & Machine Learning

We transfer cutting-edge academic & industrial research results in ML to industry applications.

ML research experience with industry leaders (Bayer AG, Swiss Re, Google Research)
Developer of popular ML library (fastFM)
Winner of high profile ML-competitions
Publications in top tier ML journals & speaker on conferences (WWW, ECML, PAKDD, JMLR)

✔ Profit from our ML-experience & expertise

Cloud Computing & Data Engineering

We build on powerful cloud computing technologies allowing us to quickly create individual & complex ML solutions.

Build on proven open source libraries (Nomad, Kubernetes, Docker, etc.)
Handles > 7 TB data per day
Secure & quickly scalable
Cross-cloud deployments
Funded by Google Cloud for Startups
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✔ Save time & costs with our advanced Tech Stack

Agile Data Science & Software Engineering

We transfer proven software development practices to data science projects to iterate at agile speed.

Early prototype & continuous improvements
Continuous integration & delivery
Peer-reviewed code & easily deployable solutions (docker container)
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✔ Work with maximum efficiency at agile speed

Management

Sonja Strothmann

CEO

Sonja holds a Master of Science in Strategic Marketing from the Maastricht University. She has worked for +9 years on diverse Digitalization Projects as IT-Manager and Consultant for known Companies. At Victorinox in Switzerland she was responsable for the Online Operations Management.

Dr. Immanuel Bayer

CTO

Immanuel holds a Diploma in Computational Engineering Sciences from the RWTH Aachen University and a PhD degree in Machine Learning & Computer Sciences from the University of Konstanz. He worked at Bayer Technology Services, Google Research in Mountain View and Swiss Re in Zurich.