Better Diagnostics for everyone

It is our goal to bring the best possible diagnostics to all people worldwide


Our Vision

Connect the dots in clinical pathways to enable improved patient outcomes

Our Mission

Create an AI enriched medical platform to assist physicians’ decision making

Our Values

What we believe in


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Technology serving humans
Our solutions support physicians to help their patients – everywhere.

Science for the cure
By combining scientifically proven methodologies with innovative technologies and by working in close collaboration with universities we can solve tough problems.

Hands-on attitude
We accept complexity and deliver results in an iterative approach from day one.

Customers as partners
We work very closely together with multiple customers to foster a thriving medical community and to leverage that knowledge to enhance our artificial intelligence platform.

Trust and transparency
Appreciation and respect among team members is the foundation for a trustful collaboration with our partners.

We are medicalvalues

Some impressions of the people behind it

Our Managing Team

Jan Kirchhoff

Jan Kirchhoff

Executive Director / Sales

Florian Stumpe

Florian Stumpe

Executive Director / Technology


Supported by mentors and industry experts

Our team gets support from expert advisors with long-term industry experience.
Martin Kopp

Martin Kopp

Former VP SAP for Healthcare

Hospital Solutions and Sales

Antje Leminsky

Former CEO Grenke AG

Financial Insights and Strategy

Michael Becker

Michael Becker

Executive Director Insurance

Risk Management and Compliance

Tobias Krick

CEO Healthcare iNNK

Marketing and Healthcare Ecosystem


Join our Ecosystem

Siemens Healthineers Logo

We constantly expand our network of software partners. Among them are StartUps and small vendors, but we are also part of the Siemens Healthineers teamplay digital health platform.

It is our goal, to create integrations based on industry standards like FHIR and we actively promote the use of taxonomies like SNOMED CT and LOINC to enable true interoperability.

We are active contributors to AI networks like the Digital Hub for Applied Artificial Intelligence Karlsruhe. In addition, we are part of networks in the medical industry like Healthcare iNNK (organized by Tobias Krick) and the 5-HT Digital Hub Chemistry & Health.


Work with us

Become a part of the medicalvalues team and connect with us the dots in clinical pathways to enable improved patient outcomes. Join a motivated interdisciplinary team to pursue our vision of providing the best possible diagnostics to people worldwide. Work with the latest technologies on an innovative product and add value to society for high-quality healthcare.

work with us - career

Senior Developer

Full-Time / Karlsruhe / (m/f/d)

Technical Consultant

Full-Time / Karlsruhe / (m/f/d)

Business Development

Working Student / Internship / (m/f/d)

One Team

Inclusion and Diversity

The success of a product depends not only on a good idea but above all on an excellent team. We as a company are convinced that the way to success is to create a culture in which everyone feels welcome and can be their true selves. We are convinced that integration strengthens diversity in the company and that diversity creates better results.

Therefore, as a company, we also take our task of inclusion very seriously. In addition to actively promoting diversity in our team, we train employees on topics such as gender equality as well as gender-appropriate language.

Blog Articles & News

Track & Trace – quality improvement for medical pre-analysis

Modern laboratory diagnostics are very precise. Thanks to highly developed measurement technology and numerous control mechanisms (precision controls, interlaboratory tests, accreditation, etc.), serious measurement errors in the laboratory are virtually impossible. Faulty laboratory results are usually not caused by faulty laboratory analysis, but are due to (human) errors in pre-analysis. Sample tracking is a useful tool for minimising errors in the pre-analytical phase and improving the classification of any measurement inaccuracies.

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