Picture a situation where a company has a spectrometer and model that is performing well in a quality control setting. The company wants to set up a second spectrometer for another line or another location. Normally, we need to wait until enough spectra and reference values are available to be able to build a competent model, which can take months, even a year. In Ai-Metrix, a customer can choose to jointly model a data-rich spectrometer with a data poor instrument. If Ai-Metrix sees a discrepancy in data amounts, it clicks in a new set of optimization parameters and builds an augmented model that should be available within days. The model will not be as good as a well-populated calibration, but the system would then dial itself in as more data becomes available. Because Ai-Metrix does not care how many models a user creates, the marginal cost for this series of model updates is essentially zero. And you can put the spectrometer to use right away.