Abstract: In some implementations, a system may receive a submission associated with an innovation associated with an entity. The system may analyze, using a first machine learning model, the submission to identify a classification associated with the innovation. The system may analyze, using a second machine learning model in association with the classification, content of the submission to identify a characteristic of the innovation. The system may determine, using a third machine learning model and based on the characteristic, a ranking of the innovation relative to individual innovations in the subset of innovations. The system may determine, using a fourth machine learning model, an impact score associated with the innovation. The system may perform, based on the impact score satisfying a threshold, an action associated with a project involving the innovation.

Abstract: In some implementations, a system may receive a submission associated with an innovation associated with an entity. The system may analyze, using a first machine learning model, the submission to identify a classification associated with the innovation. The system may analyze, using a second machine learning model in association with the classification, content of the submission to identify a characteristic of the innovation. The system may determine, using a third machine learning model and based on the characteristic, a ranking of the innovation relative to individual innovations in the subset of innovations. The system may determine, using a fourth machine learning model, an impact score associated with the innovation. The system may perform, based on the impact score satisfying a threshold, an action associated with a project involving the innovation.

Abstract: A device may receive a feature submission identifying a candidate feature for a software application. The device may pre-process the feature submission to reformat data associated with the candidate feature to match a data format associated with stored information regarding past feature submissions. The device may perform natural language processing on the data associated with the candidate feature to determine a semantic meaning of the candidate feature. The device may compare the semantic meaning of the candidate feature with an index of past feature submissions. The device may provide a response indicating whether the candidate feature matches the past feature submissions wherein the response comprises an indication that the candidate feature does not match any past feature submission or information identifying one or more past feature submissions associated with a threshold semantic similarity to the candidate feature.