Human intervention to analyse FTIR or MS spectrum is useful but to achieve the next generation of autonomous instrumentation for reaction screening, a completely automated method for determining whether a reaction occurred is required. The current approaches to automating functional group identification are similar to those applied by humans, using a set of rules and pattern (peak) matching to map spectra to a functional group . Such methods typically utilize only selected spectral regions to identify functional groups, and often afford relatively low confidence predictions owing to a limited database of known compounds . Furthermore, to our knowledge, these methods can only incorporate data from a single spectral technique (i.e., either FTIR or MS) and ignore relationships between different spectral data for identification. Hence, there is a need for automated and accurate methods capable of multiplespectra integration without the use of pre-established patterns on known databases. Such methods will need minimal-to-no human intervention towards the realization of automated synthetic robots that screen functional groups and combine spectral data to validate each step during reaction screening and multi-step automated synthesis . The state-of-the-art robot for automated reaction detection currently employs different techniques to determine the presence of a reaction , but it is limited to identify the presence of pre-defined known compounds. It is a major challenge to develop fully automated robots to discover new reactions that produce unexpected products. Our goal is to extend the capabilities of these automated synthetic robots by developing a fast, automated methodology for functional group determination that can be used in real-time, thereby enabling reaction screening through the identification of functional group changes in a database-free manner.