Abstract: The disclosed embodiments provide a system for managing a counting use case. During operation, the system matches, to a first counting use case, a first parameter of a first unified request over an application programming interface (API) provided by a unified counting platform. Next, the system identifies, based on metadata for configuring the first counting use case in the unified counting platform, a first counting solution assigned to the first counting use case. The system then formats a first set of parameters in the first unified request into a first adapted request that is transmitted to the first counting solution. The system also formats a first response to the first adapted request from the first counting solution into a first unified response to the first unified request. Finally, the system transmits the first unified response to a first source of the first unified request.

Abstract: The disclosed embodiments provide a system for managing a counting use case. During operation, the system matches, to a first counting use case, a first parameter of a first unified request over an application programming interface (API) provided by a unified counting platform. Next, the system identifies, based on metadata for configuring the first counting use case in the unified counting platform, a first counting solution assigned to the first counting use case. The system then formats a first set of parameters in the first unified request into a first adapted request that is transmitted to the first counting solution. The system also formats a first response to the first adapted request from the first counting solution into a first unified response to the first unified request. Finally, the system transmits the first unified response to a first source of the first unified request.

Abstract: Techniques for implementing a self-serve content classification platform are provided. In one technique, through a user interface (UI) of the content classification platform, a user selects an option corresponding to a particular processor type. A processor configuration is also received through the same or different UI. Based on the user selection and the processor configuration, processor data that associates the particular processor type and the processor configuration is stored in association with a client context. A content classification request is received from a client associated with the client context. In response to receiving the content classification request, content that is referenced by the content classification request is identified, the processor data is accessed based on the content classification request, a processor that is defined based on the processor data is caused to be executed based on the content, and a result is generated based on output from the processor.

Abstract: Techniques for implementing a self-serve content classification platform are provided. In one technique, through a user interface (UI) of the content classification platform, a user selects an option corresponding to a particular processor type. A processor configuration is also received through the same or different UI. Based on the user selection and the processor configuration, processor data that associates the particular processor type and the processor configuration is stored in association with a client context. A content classification request is received from a client associated with the client context. In response to receiving the content classification request, content that is referenced by the content classification request is identified, the processor data is accessed based on the content classification request, a processor that is defined based on the processor data is caused to be executed based on the content, and a result is generated based on output from the processor.