Abstract: The present disclosure relates to an intelligent quote-to-cash software agent (“the Agent”) that enables users to efficiently interface with a quote-to-cash system from external messaging applications. The Agent is able to communicate with users using natural language and to identify quote-to-cash system action requests and associated parameters from natural language communications. The user may communicate with the Agent from one of plurality of messaging applications that are not associated with the quote-to-cash system. In response to identifying a quote-to-cash action request and associated parameters in a communication session with a user, the Agent calls the quote-to-cash system and obtains the applicable quote-to-cash output requested by the user. The Agent forwards the quote-to-cash system output to the user via the external messaging application selected by the user. The Agent may initiate communications with the user to inform the user of an opportunity in the quote-to-cash process.

Abstract: The present disclosure describes a system, method, and computer program for real-time and computationally efficient calculation of a recommended value range for a quote variable, such as price, discount, volume, or closing time. The system uses the highest-density interval (HDI) of probability density function (PDF) as a recommended or suggested value range for a quote variable. PDFs for the quote variable are precomputed for groups of related inputs, and each PDF is summarized as an array of discrete points. A dimension reduction technique is applied to the PDF inputs in both the training and real-time (non-training) phases to reduce the number of possible combinations of PDFs. During a quote-creation process, a PDF look-up table enables the system to efficiently identify an applicable PDF from the group of precomputed PDFs based on reduced input values.

Abstract: The present disclosure relates to an intelligent quote-to-cash software agent (“the Agent”) that enables users to efficiently interface with a quote-to-cash system from external messaging applications. The Agent is able to communicate with users using natural language and to identify quote-to-cash system action requests and associated parameters from natural language communications. The user may communicate with the Agent from one of plurality of messaging applications that are not associated with the quote-to-cash system. In response to identifying a quote-to-cash action request and associated parameters in a communication session with a user, the Agent calls the quote-to-cash system and obtains the applicable quote-to-cash output requested by the user. The Agent forwards the quote-to-cash system output to the user via the external messaging application selected by the user. The Agent may initiate communications with the user to inform the user of an opportunity in the quote-to-cash process.

Abstract: The present disclosure relates to an intelligent quote-to-cash software agent (“the Agent”) that enables users to efficiently interface with a quote-to-cash system from external messaging applications. The Agent is able to communicate with users using natural language and to identify quote-to-cash system action requests and associated parameters from natural language communications. The user may communicate with the Agent from one of plurality of messaging applications that are not associated with the quote-to-cash system. In response to identifying a quote-to-cash action request and associated parameters in a communication session with a user, the Agent calls the quote-to-cash system and obtains the applicable quote-to-cash output requested by the user. The Agent forwards the quote-to-cash system output to the user via the external messaging application selected by the user. The Agent may initiate communications with the user to inform the user of an opportunity in the quote-to-cash process.

Abstract: This disclosure relates to a system, method, and computer program that enables users to initiate quote-to-cash system actions and receive quote-to-cash system output via a virtual/augmented reality interface. A virtual reality client device provides a virtual/augmented reality user interface via which the user can initiate one of a plurality of quote-to-cash action requests, such as requesting a quote or configuring a product. In response to the user selecting a quote-to-cash action, the client device displays a virtual/augmented scene with graphical images that correspond to parameters of a quote-to-cash action. The user is able to specify parameters for the quote-to-cash action by interacting with these images in the virtual/augmented reality scene.

Abstract: The present disclosure describes a system, method, and computer program for real-time and computationally efficient calculation of a recommended value range for a quote variable, such as price, discount, volume, or closing time. The system uses the highest-density interval (HDI) of probability density function (PDF) as a recommended or suggested value range for a quote variable. PDFs for the quote variable are precomputed for groups of related inputs, and each PDF is summarized as an array of discrete points. A dimension reduction technique is applied to the PDF inputs in both the training and real-time (non-training) phases to reduce the number of possible combinations of PDFs. During a quote-creation process, a PDF look-up table enables the system to efficiently identify an applicable PDF from the group of precomputed PDFs based on reduced input values.

Abstract: The present disclosure describes a system, method, and computer program for real-time and computationally efficient calculation of a recommended value range for a quote variable, such as price, discount, volume, or closing time. The system uses the highest-density interval (HDI) of probability density function (PDF) as a recommended or suggested value range for a quote variable. PDFs for the quote variable are precomputed for groups of related inputs, and each PDF is summarized as an array of discrete points. A dimension reduction technique is applied to the PDF inputs in both the training and real-time (non-training) phases to reduce the number of possible combinations of PDFs. During a quote-creation process, a PDF look-up table enables the system to efficiently identify an applicable PDF from the group of precomputed PDFs based on reduced input values.

Abstract: The present disclosure describes a system, method, and computer program for real-time and computationally efficient calculation of a recommended value range for a quote variable, such as price, discount, volume, or closing time. The system uses the highest-density interval (HDI) of probability density function (PDF) as a recommended or suggested value range for a quote variable. PDFs for the quote variable are precomputed for groups of related inputs, and each PDF is summarized as an array of discrete points. A dimension reduction technique is applied to the PDF inputs in both the training and real-time (non-training) phases to reduce the number of possible combinations of PDFs. During a quote-creation process, a PDF look-up table enables the system to efficiently identify an applicable PDF from the group of precomputed PDFs based on reduced input values.

Abstract: The present disclosure relates to an intelligent quote-to-cash software agent (“the Agent”) that enables users to efficiently interface with a quote-to-cash system from external messaging applications. The Agent is able to communicate with users using natural language and to identify quote-to-cash system action requests and associated parameters from natural language communications. The user may communicate with the Agent from one of plurality of messaging applications that are not associated with the quote-to-cash system. In response to identifying a quote-to-cash action request and associated parameters in a communication session with a user, the Agent calls the quote-to-cash system and obtains the applicable quote-to-cash output requested by the user. The Agent forwards the quote-to-cash system output to the user via the external messaging application selected by the user. The Agent may initiate communications with the user to inform the user of an opportunity in the quote-to-cash process.

Abstract: This disclosure relates to a system, method, and computer program that enables users to initiate quote-to-cash system actions and receive quote-to-cash system output via a virtual/augmented reality interface. A virtual reality client device provides a virtual/augmented reality user interface via which the user can initiate one of a plurality of quote-to-cash action requests, such as requesting a quote or configuring a product. In response to the user selecting a quote-to-cash action, the client device displays a virtual/augmented scene with graphical images that correspond to parameters of a quote-to-cash action. The user is able to specify parameters for the quote-to-cash action by interacting with these images in the virtual/augmented reality scene.