We develop software in the area of analytical quality assurance. Typically, starting from data obtained from measurements, our software products avail themselves of state-of-the-art statistical methods to evaluate the accuracy and the sensitivity of the measurement instrument or method involved.
Emblematic not only of our software development activities, but indeed of QuoData's interdisciplinary expertise, our flagship product PROLab is a unique and sophisticated tool for the implementation and analysis of interlaboratory studies, especially for laboratory assessment and method evaluation.
Our international and ever-growing clientele consists of private and governmental research institutes, proficiency test providers, universities, laboratories, and includes:
- the FDA (USA)
- the Federal Office for Consumer Protection and Food Safety (Germany)
- the Health and Safety Laboratory (England)
- the Institute of Reference Materials and Measurements (Belgium)
- the European Commission.
Furthermore, we offer consultancy services and develop customized software that meets requirements specified by our customers. Two examples of such specially conceived software (in this case the area of application is risk and trend analysis) will be found in the section for Environmental Monitoring.
Software for interlaboratory studies
These professional and flexible software products were specially designed to help you with the preparation, the performance and the evaluation of interlaboratory tests.
Further information about our software for interlaboratory studies.
Interested in getter even more out of PROLab? See our Add-ons for PROLab:
Software for in-house validation
InterVal and InterVal Plus enable you to carry out a comprehensive validation of in-house methods. Their statistical evaluation follows the computation prescriptions set forth in Commission Decision 2002/657/EC.
Further information about our software for in-house validation.
Software for the determination of measurement uncertainty - GUMsim
GUMsim is a software tool for the determination of measurement uncertainty in connection with the examination or calibration of measurement instruments or processes.
The various algorithms and computational procedures involved are based on the current GUM-document and the supplement (GUM-S1), which deals with the application of the Monte-Carlo method.