Abstract: The subject disclosure encompasses solutions for matching customer information with customer reviews. A process of the disclosed technology includes steps for aggregating customer data associated with a customer, retrieving a plurality of customer reviews, wherein each of the customer reviews describe customer satisfaction with a service provided by a corresponding service provider, extracting review metadata for each of the plurality of customer reviews, and matching the customer with at least one of the customer reviews based on the customer data and the extracted review metadata. Systems and machine-readable media are also provided.

Abstract: Systems, methods, and computer program products for generating job value predictions by a trained model for a tenant include receiving live data associated with a tenant, where the live data includes information associated with a job to be performed by the tenant. A trained model associated with the tenant is retrieved, where the trained model is configured to generate a job value prediction for the job to be performed. The live data is preprocessed to obtain a set of features associated with the job, the set of features consumable by the trained model, and the trained model is applied to the set of features to generate the job value prediction for the job to be performed by the tenant.

Abstract: Aspects of the present disclosure involve systems, methods, computer program products, and the like, for managing software telephones and telephone services, such as customer service support or sales, for multiple clients. Methods consistent with the present disclosure may be implemented as non-transitory computer-readable storage medium, where a processor executes instructions out of a memory when services are provided or organized during a telephone call or a text message communication session. In general, a telephone or text messaging service may be managed along multiple different components including origination services, platform services, and termination services without introducing additional conferencing and/or secondary voice conferencing sessions to calls between clients and respective customers.

Abstract: The subject disclosure relates to techniques for monitoring and managing pricebooks, for example between tenants and suppliers. A process of the disclosed technology can include steps for receiving transaction event data corresponding to an interaction of one of a supplier or a tenant with one of a master pricebook or a tenant pricebook, determining at least one change between the transaction event data and a previously stored version of data associated with the one of the supplier or the tenant, and generating a set of changes based on the at least one change.

Abstract: Aspects of the present disclosure involve systems, methods, computer program products, and the like, for managing software telephones and telephone services, such as customer service support or sales, for multiple clients. Methods consistent with the present disclosure may be implemented as non-transitory computer-readable storage medium, where a processor executes instructions out of a memory when services are provided or organized during a telephone call or a text message communication session. In general, a telephone or text messaging service may be managed along multiple different components including origination services, platform services, and termination services without introducing additional conferencing and/or secondary voice conferencing sessions to calls between clients and respective customers.

Abstract: Systems, methods, and computer program products for generating job value predictions by a trained model for a tenant include receiving live data associated with a tenant, where the live data includes information associated with a job to be performed by the tenant. A trained model associated with the tenant is retrieved, where the trained model is configured to generate a job value prediction for the job to be performed. The live data is preprocessed to obtain a set of features associated with the job, the set of features consumable by the trained model, and the trained model is applied to the set of features to generate the job value prediction for the job to be performed by the tenant.