Quality

The best of both worlds. Human and Artificial Intelligence.

The interaction between humans and AI offers the best of both worlds. This combination enables us to meet the highest standards of performance and safety as a medical device.

Highest quality through clearly defined processes.

Proven quality

All our solutions are certified as Class IIa medical devices and therefore meet the highest quality and safety standards in the industry.

Technological innovation

We use technology where it makes sense. By leveraging AI, we can automatically analyze and process millions of medical publications to create the baseline for our algorithms.

Perfect symbiosis

The practical knowledge of doctors combined with millions of medical publications and groundbreaking technology create the perfect symbiosis between humans and AI.

Trust is good, control is better.

Medical device with CE certification Quality management according to ISO 13485 Information security management according to ISO 27001 Standardized processes and norms

Medical device with CE certification

Our technology is certified as a Class IIa medical device. This means that an independent Notified Body, in our case TÜV Süd, verifies our compliance with norms and standards in annual audits.

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Quality management according to ISO 13485

The safety of our products has absolute priority for us, therefore all key processes in the company are certified according to ISO 13485:2016. This quality management system ensures that the highest standards of performance and safety are reliably met.

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Information security management according to ISO 27001

As part of our commitment to data security, XUND is ISO 27001:2013 certified. We have taken this step to ensure that our Information Security Management System adheres to international data privacy standards – protecting the most valuable information.

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Standardized processes and norms

Being a medical device manufacturer, we have to adhere to a large number of regulatory requirements, which are ensured by compliance with standards. In addition to the ISO 13485-compliant quality management system, we meet the requirements of the following relevant standards, directives and laws:

Medical Devices Regulation (MDR) 2017/745
Medical Devices Act and relevant regulations
EN ISO 14971:2019
EN 62304:2006 + A1:2015
EN 62366-1:2015
EN 82304-1:2017

In addition to this, we comply with all local regulations in countries where we market our product.

Committed to security and data protection.

State-of-the-art encryption methods

By using state-of-the-art encryption methods when transferring and storing health information, we guarantee the security and privacy of sensitive data.

Sophisticated database architecture

We prevent unauthorized access to data through structural and technological barriers. No one other than the user can view personal health data.

Data centers in Austria and Switzerland

By relying on local storage with certified data centers, we ensure that no sensitive information leaves the European legal area.

The knowledge of millions built into one health solution.

Data analysis with AI

Our artificial intelligence can analyze millions of medical publications from the literature and process data on over 4.000 medical conditions.

Review by doctors

Our team of doctors then verifies this information qualitatively and enriches it with reference literature and practical experience.

Medical stress test

We verify our technology with thousands of real life case studies. This is the most objective way to test accuracy of our system.

Usability tests

Through ongoing testing with real users, we ensure that our medical algorithms work as intended and meet the defined requirements.

Convincing medical accuracy and reliability.

We verify the medical accuracy of our technology in medical stress tests. This happens continuously and on the basis of thousands of case studies from the literature. The goal is to identify the verified diagnosis from the case study as a possible outcome. This has proven to be the most reliable method of testing medical accuracy under objective conditions.

Medical accuracy

93.3 %

Tested with case studies by Semigran et al. 2015.

Benchmark with case studies from the standard literature.

In order to objectively assess the quality of XUND also in comparison to other solutions, we assessed the 45 case studies from one of the most frequently cited publications in the domain. These case studies are regularly used by researchers to evaluate medical accuracy, most recently by Ceney et al. 2021.

ICD-10J00

Medical conditionCommon cold

Age30 Years

Result identified

30-year-old male with common cold

ICD-10: J00

Present symptoms:

Runny nose
Sore throat
Increased sweating
Headache
Cough
General muscle pain
Limb pain
Red throat
Swelling of the lymph nodes

Additional information:

Do you smoke or have you been a smoker in the past?

Yes

Source:

Intermittent low back pain referred from a uterine adenomyosis: a case report. J Chiropr Med. 2011;10(1):64-69. https://dx.doi.org/10.1016%2Fj.jcm.2010.08.004

Verified diagnosis identified as 3. result

Conditions identified by XUND:

Acute bronchitis
Pharynx inflammation
Common cold

ICD-10B27.0

Medical conditionPfeiffer's disease

Age16 Years

Result identified

16-year-old female with Pfeiffer's disease

ICD-10: B27.0

Present symptoms:

Fever
Sore throat
Physical exhaustion
Swallowing difficulties
General malaise
Swelling of the lymph nodes
Red throat
Rash

Additional information:

Do you feel like the rash is spreading to your whole body?

Yes

Source:

Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015

Verified diagnosis identified as 2. result

Conditions identified by XUND:

Scarlet fever
Pfeiffer's disease
COVID-19 infection

ICD-10J02

Medical conditionPharynx inflammation

Age7 Years

Result identified

7-year-old female with pharynx inflammation

ICD-10: J02

Present symptoms:

Fever
Sore throat
Nausea
Vomiting
Swelling of the lymph nodes
Red throat

Source:

Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015

Verified diagnosis identified as 2. result

Conditions identified by XUND:

Tonsil inflammation
Pharynx inflammation
COVID-19 infection

ICD-10H66

Medical conditionInflammation of the middle ear

Age2 Years

Result identified

2-year-old male with inflammation of the middle ear

ICD-10: H66

Present symptoms:

Sniffles
Cough
Sleeping difficulties
Loss of appetite
Fever

Source:

Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015

Verified diagnosis identified as 2. result

Conditions identified by XUND:

Acute bronchitis
Otitis media of the infant or toddler
Common cold
COVID-19 infection

ICD-10D59.3

Medical conditionHemolytic uremic syndrome

Age4 Years

Result not identified

4-year-old male with hemolytic uremic syndrome

ICD-10: D59.3

Present symptoms:

Sniffles
Cough
Sleeping difficulties
Loss of appetite
Fever
Irritability
Runny nose

Source:

Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015

Verified diagnosis could not be identified

Conditions identified by XUND:

Rotavirus
Norovirus

Always one step ahead.

In the most recent study conducted by Ceney et al. 2021, 12 symptom assessment tools were analyzed and compared with each other. The correct condition was identified in only 51% of the cases by our competitors. On average, 22,2 questions were required before a decision could be made.

Using the same data set from the study, XUND identifies the correct condition in 91,1% of cases and asks an average of only 20,3 questions. This outperforms all comparable solutions in medical accuracy and most of them in process speed.

Go to study

You want to know more? We have collected some of the most frequently asked questions for you.

Do you work together with medical doctors?

Yes, the medical team at XUND plays a pivotal role in managing the medical database, which forms the core of our AI solution. Our medical doctors verify the quality of every single piece of information in the medical database, ensuring its accuracy and reliability. This thorough verification process relies on reference literature and real-world medical practice experience. Learn more about the work of our medical team on our Medical Quality page, or read the interview with our Head of Medical.

How do you ensure the quality of the medical content?

Our in-house team of medical doctors and editors meticulously reviews and validates XUND's medical content before release, ensuring it meets ISO 13485 & MDR standards, and guaranteeing its highest quality. Additionally, the team collaborates with the Thieme Group to create fact sheets for frequently diagnosed conditions. On top of that, we continuously verify the medical accuracy of our technology through stress tests, drawing from thousands of literature case studies. For more details on our quality assurance process, please visit our Medical Quality page.

Is all content created or reviewed by medical doctors?

Yes, XUND's content is a blend of quantitative AI analysis and qualitative medical expertise. Using AI, we have analyzed millions of medical publications, which were then reviewed by our medical doctors with both literature and practical experience. This synergy, combined with our standardized quality assurance, ensures the highest level of accuracy and reliability in our content. To gain more insight into our medical quality processes, please see our Medical Quality page.

What diseases do you cover?

Our AI has the capability to automatically analyze millions of medical publications and process data on over 4,000 medical conditions. XUND prioritizes the most common medical conditions from this dataset, totaling over 500 illnesses, to provide statistically relevant and meaningful results.

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