Abstract: Technical methods, devices, and systems disclosed herein provide a predictive case-solvability score service. The predictive case-solvability score service generates case solvability scores for cases, detects events that signal those scores should be updated, updates a machine-learning model over time to ensure current trends in recent data are reflected, and identifies specific actions to recommend for increasing those scores. Furthermore, the predictive case-solvability score service provides an interface that allows users to perceive trends in case-solvability scores over time and to execute some of the specific recommended actions.

Abstract: A system for automated review of public safety incident reports include receiving structured incident data for an incident report from a submitting public safety officer including incident type information for the incident, receiving unstructured incident narrative text describing the incident, accessing an unstructured incident narrative feedback checking model applicable to incidents of the incident type, applying the model to the narrative text in light of supplemental information in the structured incident data or obtained from another source, identifying, by application of the model, matters in the narrative text likely to be flagged for correction by a human reviewer during a subsequent review, and providing feedback notifying the officer of the identified matters. The model may be retrained based on feedback or corrections provided by the officer in response to the notification of the identified matters or in response to requests for correction subsequently received from human reviewers.

Abstract: An analysis engine of an anomaly detection system receives a communication associated with an inmate in a correctional facility, evaluates a keyword identified within the communication using an anomaly detection model, and determines whether the keyword is an anomaly indicating a potential activity associated with the inmate. In response to determining that the keyword is an anomaly, the analysis engine generates an alert for the anomaly, determines an authority to notify, and notifies the authority with the generated alert. The analysis engine may receive a feedback rating for the anomaly and may update the anomaly detection model using the feedback rating. In this way the accuracy of the anomaly detection system may be improved over time. The anomaly detection models may include general data, inmate-specific data, and parameters associated with the data. The parameters associated with the data may include a weight parameter or a threshold value.

Abstract: A system for automated review of public safety incident reports include receiving structured incident data for an incident report from a submitting public safety officer including incident type information for the incident, receiving unstructured incident narrative text describing the incident, accessing an unstructured incident narrative feedback checking model applicable to incidents of the incident type, applying the model to the narrative text in light of supplemental information in the structured incident data or obtained from another source, identifying, by application of the model, matters in the narrative text likely to be flagged for correction by a human reviewer during a subsequent review, and providing feedback notifying the officer of the identified matters. The model may be retrained based on feedback or corrections provided by the officer in response to the notification of the identified matters or in response to requests for correction subsequently received from human reviewers.