Abstract: A method for generating synthetic messages for training an AI model of a communications services platform includes generating, by a communication services platform, one or more example messages simulating communications of a customer of the platform with a user associated with the customer. Each example message may be associated with a first message category. The method includes generating a prompt that includes a command to generate a synthetic message based on the example messages. The method includes causing a first AI model, in response to receiving the prompt, to generate one or more synthetic messages. The method includes generating a training dataset that includes the synthetic messages. Each item of training data of the training dataset includes the first message category as a target output label. The method includes training, using the training dataset, a second AI model to classify input messages into two or more message categories.

Abstract: A method for real-time classification quality evaluation for a communication services platform includes receiving one or more messages to be transmitted to respective destinations. The method includes determining, using a first AI model, a corresponding first message category for each message of the one or more messages. The method includes determining, using a second AI model, a corresponding second message category for each message of the one or more messages. The method includes determining a value of a performance metric of the first AI model by comparing, for each message, the corresponding first message category and the second message category. The method includes, responsive to determining that the value of the performance metric does not satisfy a predefined quality condition, modifying one or more parameters of the first AI model to improve a value of a performance metric of the first AI model.

Abstract: A method for location, consent, and reassigned identifier management for a communication services platform includes receiving, from a customer of the platform, a first messaging request to transmit a first message. The platform determines whether a first communication endpoint identifier of the request is associated with an opt-out indicator. If not, the method includes determining whether a message category associated with the first message is subject to a time-of-day restriction. If the message category is subject to the time-of-day restriction, the method includes determining whether a current time of day complies with the time-of-day restriction. If the current time of day complies with the time-of-day restriction, the method includes causing the first message to be transmitted to the communication endpoint.

Abstract: Systems and methods for channel selection and personalization based on machine learning models are described herein. The system receives a request to transmit a message to a recipient and identifies destination endpoint identifiers associated with the recipient. The system retrieves historical messaging data from a data store and extracts features comprising message volume metrics and channel-specific delivery metrics. The system associates the recipient with a cluster of recipients based on the extracted features and retrieves channel preference rankings for the cluster. The system selects a communication channel and destination endpoint identifier based on the channel preference rankings, then transmits the message via the selected channel. The system groups recipients based on messaging behavior similarities and derives channel preference rankings from historical delivery success rates and recipient engagement rates within each cluster.

Abstract: Data-driven operating model (DDOM) systems and techniques are described to manage implementation, access, and promotion of digital services by a service provider system. In one example, the DDOM system includes a data aggregation module, a journey manager module and a segment manager module. The data aggregation module supports a unified data architecture that is then leverage by the journey and segment manager modules to support matrixed journey stage and segmentation of a data lake to provide insights that are not possible by a human being alone, that are usable to manage implementation, access, and promotion of digital services by a service provider system.