CPC G06Q 10/06393 (2013.01) [G06F 16/243 (2019.01); G06F 16/3344 (2019.01); G06F 40/30 (2020.01); G06Q 10/06315 (2013.01)] | 9 Claims |
1. A computer-implemented method comprising:
deducing, by an NLP, an intent and one or more entities from an oral query;
obtaining, by a fulfillment application program interface (F-API), data associated with the intent and the one or more entities from a database, the F-API comprising a business summary module, a business metrics detail module and a business metrics contributing factor module;
configuring access to the business metrics contributing factor module after at least one of the business summary module and the business metric detail module;
in response to a first type of intent:
grouping and summarizing, by the business summary module, the data associated with the intent and the one or more entities;
providing, by the business summary module, one or more insights into the data; and
forming, by the business summary module, a first conversational response to the user;
in response to a second type of intent:
setting, by the business metric detail module, a time horizon for the one or more entities;
gathering, by the business metric detail module, data related to the one or more entities for the time horizon;
gathering, by the business metric detail module, data related to the one or more entities for a future time horizon;
providing, by the business metric detail module, a comparison of the data for the time horizon with the data for the future time horizon; and
forming, by the business metric detail module, a second conversational response to the user comprising the comparison;
in response to a third type of intent:
identifying, by the business metrics contributing factor module, a subset of the one or more entities based on a previous dialogue involving at least one of the business summary module and the business metrics detail module;
obtaining, by the business metrics contributing factor module, further information about the subset;
grouping and summarizing, by the business metrics contributing factor module, data related to subset; and
forming, by the business metrics contributing factor module, a third conversational response to the user comprising information about data that has not been previously conveyed by either the business summary module or the business metrics detail module;
and
sending, by the F-API, each of the first, second and third conversational responses for voice output through a communication channel.
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