Abstract: The present invention is related to a system and method for automatic updates of customer relationship management and enterprise resource planning fields with the next best actions using machine learning. A system processing unit (106) of a server computer (104), executes computer-readable instructions to retrieve data from a customer relationship management database (102), a calls log and email database (108), an enterprise resource planning database (110), and data from external sources. The system processing unit (106) executes computer-readable instruction to integrate all data into the datasets and feed the datasets into a machine learning analytical module to train the machine learning analytical module. The trained machine learning analytical module analyses various information that suggests the next best actions to be taken.

Abstract: A conversational system and a method for personalized query and interaction set generation. The conversational system includes a system server, a business database server, a user device. The system server further includes a system processing unit. The data points are extracted by a system processing unit from a business database server. The system processing unit creates improved multiple datasets that include the grammatically correct query, corresponding responses of the grammatically correct query, and corresponding data points related to the grammatically correct query. The multiple datasets are being fed into the conversational module to train the conversational module. The user sends queries to the system server through the user device. The system processing unit sends a query to the conversational module. The conversation module sends the query to a search engine that searches data and sends data to an answer generating module to send the answer to the user.

Abstract: The present invention relates to a system (100) and method for automated sales forecast on an aggregate level during the black swan scenario. The present invention includes a computational unit (102), and a display unit (108). In an embodiment, the computational unit (102) including, but limited to, a desktop computer, a laptop, a tablet, a smartphone, a mobile phone. The computational unit (102) includes a database unit (104) and a system processing unit (106). The system processing unit (106) executes computer-readable instructions to collect the company data through the company servers and the system processing unit (106) further executes computer-readable instruction to forecast sales of the company on an aggregate level during the black swan scenario. The system processing unit (106) executes computer-readable instructions to provide a comprehensive analysis of forecasts from the top-down level that serves the basis for the Finance Team/CSO/CFO to set modified targets.

Abstract: The present invention relates to a method and system for automated sales forecast on a deal level during the black swan scenario. A list of features is being generated that influence the sales forecast on the deal level. The data related to a list of features are processed and transformed into an appropriate form through feature engineering. The artificial intelligence-based model is being selected and trained by the feeding data. The artificial intelligence-based model is optimized with the help of hyper parameter values. The artificial intelligence-based model uses previous data and generates probability scores, forecast close date postponement, and forecast amount on which sale deal would close. Thus, based on the above forecast, overall sales on the deal level are being forecasted. The artificial intelligence-based model is trained and deployed for the sales forecast on the deal level with the help of a computational unit.