Artificial intelligence and machine learning based conversational agent

1. An apparatus for implementing an artificial intelligence and machine learning based conversational agent comprising:

at least one hardware processor; and

a non-transitory computer readable medium having stored thereon machine readable instructions, the machine readable instructions, when executed by the at least one hardware processor, cause:

a user request analyzer, executed by the at least one hardware processor, to

ascertain, based on a chat conducted with a conversational chatbot, a request by a user to purchase a product;

a user attribute analyzer, executed by the at least one hardware processor, to

ascertain an attribute associated with the user;

a purchase request controller, executed by the at least one hardware processor, to

generate, based on an analysis of the request by the user to purchase the product and the attribute associated with the user, an intent associated with the user to purchase the product,

generate, based on the intent associated with the user to purchase the product, a catalog that includes a plurality of products that match the request by the user to purchase the product by training, based on historical data, a convolution neural network (CNN) with a long short-term memory (LSTM) layer machine learning classifier,

receive selection of a product from the plurality of products,

receive identification of a quantity associated with the selected product, and

generate, based on the received selection of the product from the plurality of products and the received identification of the quantity associated with the selected product, a purchase request by

determining, based on the received selection of the product from the plurality of products and the received identification of the quantity associated with the selected product, whether sufficient funds are available for purchase of the selected product, and

based on a determination that sufficient funds are available for purchase of the selected product, generating the purchase request; and

a purchase order controller, executed by the at least one hardware processor, to

generate, based on the purchase request, a purchase order associated with the selected product, and

procure, based on the purchase order associated with the selected product, the selected product for the user.

2. The apparatus for implementing the artificial intelligence and machine learning based conversational agent according to claim 1 , wherein the machine readable instructions, when executed by the at least one hardware processor, further cause:

a purchase request status analyzer, executed by the at least one hardware processor, to

ascertain, based on a further chat conducted with the conversational chatbot to request a status of the purchase request, a purchase request status with respect to the purchase request, and

generate, based on the purchase request status, a display of a specified number of previous purchase request transactions associated with the user.

3. The apparatus for implementing the artificial intelligence and machine learning based conversational agent according to claim 1 , wherein the machine readable instructions, when executed by the at least one hardware processor, further cause:

a purchase request status analyzer, executed by the at least one hardware processor, to

ascertain, based on a further chat conducted with the conversational chatbot to request a status of the purchase request, a purchase request status with respect to a purchase request number associated with the purchase request, and

generate, based on the purchase request status, a display of a previous purchase request transaction associated with the purchase request number.

4. The apparatus for implementing the artificial intelligence and machine learning based conversational agent according to claim 1 , wherein the machine readable instructions, when executed by the at least one hardware processor, further cause:

a purchase order status analyzer, executed by the at least one hardware processor, to

ascertain, based on a further chat conducted with the conversational chatbot to request a status of the purchase order, a purchase order status with respect to the purchase order, and

generate, based on the purchase order status, a display of a specified number of previous purchase order transactions associated with the user.

5. The apparatus for implementing the artificial intelligence and machine learning based conversational agent according to claim 1 , wherein the machine readable instructions, when executed by the at least one hardware processor, further cause:

a purchase order status analyzer, executed by the at least one hardware processor, to

ascertain, based on a further chat conducted with the conversational chatbot to request a status of the purchase order, a purchase order status with respect to a purchase order number associated with the purchase order, and

generate, based on the purchase order status, a display of a previous purchase order transaction associated with the purchase order number.

6. The apparatus for implementing the artificial intelligence and machine learning based conversational agent according to claim 1 , wherein the user request analyzer is executed by the at least one hardware processor to ascertain, based on the chat conducted with the conversational chatbot, the request by the user to purchase the product by:

converting, for the chat conducted with the conversational chatbot, a speech input to text or a text input to speech, to ascertain the request by the user to purchase the product.

7. The apparatus for implementing the artificial intelligence and machine learning based conversational agent according to claim 1 , wherein the machine readable instructions, when executed by the at least one hardware processor, further cause:

a user profile controller, executed by the at least one hardware processor, to

ascertain, based on a further chat conducted with the conversational chatbot to request a user profile associated with the user, user profile details of the user profile associated with the user.

8. The apparatus for implementing the artificial intelligence and machine learning based conversational agent according to claim 7 , wherein the user profile details include

leave requests associated with the user.

9. The apparatus for implementing the artificial intelligence and machine learning based conversational agent according to claim 7 , wherein the user profile controller is further executed by the at least one hardware processor to:

modify, based on the further chat conducted with the conversational chatbot to request a modification to the user profile associated with the user, the user profile details of the user profile associated with the user.

10. The apparatus for implementing the artificial intelligence and machine learning based conversational agent according to claim 1 , wherein the purchase request controller is executed by the at least one hardware processor to generate, based on the analysis of the request by the user to purchase the product and the attribute associated with the user, the intent associated with the user to purchase the product, and generate, based on the intent associated with the user to purchase the product, the catalog that includes the plurality of products that match the request by the user to purchase the product by:

training, based on the historical data, the CNN with the LSTM layer machine learning classifier by implementing

forward propagation by inputting a training sample of a known flag into the CNN followed by a recurrent LSTM layer to obtain an output result, and

back propagation on a difference between the output result and the known flag to correct weights of the CNN;

generating, based on the analysis of the request by the user to purchase the product and the attribute associated with the user using the trained machine learning classifier, the intent associated with the user to purchase the product by performing

forward propagation by inputting an object to be classified into the CNN followed by the recurrent LSTM layer to obtain another output result, and

classification of the object to be classified based on the another output result; and

generating, based on an analysis of the intent associated with the user to purchase the product using the trained machine learning classifier, the catalog that includes the plurality of products that match the request by the user to purchase the product.

11. A method for implementing an artificial intelligence and machine learning based conversational agent comprising:

ascertaining, by at least one hardware processor and based on a chat conducted with a conversational chatbot, a request by a user to purchase a product;

ascertaining, by the at least one hardware processor, an attribute associated with the user;

training, by the at least one hardware processor and based on historical data, a convolution neural network (CNN) with a long short-term memory (LSTM) layer machine learning classifier;

generating, by the at least one hardware processor and based on an analysis of the request by the user to purchase the product and the attribute associated with the user using the trained machine learning classifier, an intent associated with the user to purchase the product;

generating, by the at least one hardware processor and based on an analysis of the intent associated with the user to purchase the product using the trained machine learning classifier, a catalog that includes a plurality of products that match the request by the user to purchase the product;

receiving, by the at least one hardware processor, selection of a product from the plurality of products;

receiving, by the at least one hardware processor, identification of a quantity associated with the selected product;

generating, by the at least one hardware processor and based on the received selection of the product from the plurality of products and the received identification of the quantity associated with the selected product, a purchase request by

determining, based on the received selection of the product from the plurality of products and the received identification of the quantity associated with the selected product, whether sufficient funds are available for purchase of the selected product, and

based on a determination that sufficient funds are available for purchase of the selected product, generating the purchase request;

generating, by the at least one hardware processor and based on the purchase request, a purchase order associated with the selected product; and

procuring, by the at least one hardware processor and based on the purchase order associated with the selected product, the selected product for the user.

12. The method according to claim 11 , further comprising:

ascertaining, by the at least one hardware processor and based on a further chat conducted with the conversational chatbot to request a status of the purchase request, a purchase request status with respect to the purchase request; and

generating, by the at least one hardware processor and based on the purchase request status, a display of a specified number of previous purchase request transactions associated with the user.

13. The method according to claim 11 , further comprising:

ascertaining, by the at least one hardware processor and based on a further chat conducted with the conversational chatbot to request a status of the purchase request, a purchase request status with respect to a purchase request number associated with the purchase request; and

generating, by the at least one hardware processor and based on the purchase request status, a display of a previous purchase request transaction associated with the purchase request number.

14. The method according to claim 11 , further comprising:

ascertaining, by the at least one hardware processor and based on a further chat conducted with the conversational chatbot to request a status of the purchase order, a purchase order status with respect to the purchase order; and

generating, by the at least one hardware processor and based on the purchase order status, a display of a specified number of previous purchase order transactions associated with the user.

15. The method according to claim 11 , further comprising:

ascertaining, by the at least one hardware processor and based on a further chat conducted with the conversational chatbot to request a status of the purchase order, a purchase order status with respect to a purchase order number associated with the purchase order; and

generating, by the at least one hardware processor and based on the purchase order status, a display of a previous purchase order transaction associated with the purchase order number.

16. A non-transitory computer readable medium having stored thereon machine readable instructions, the machine readable instructions, when executed by at least one hardware processor, cause the at least one hardware processor to:

ascertain, based on a chat conducted with a conversational chatbot, a request by a user to purchase a product;

ascertain an attribute associated with the user;

generate, based on an analysis of the request by the user to purchase the product and the attribute associated with the user, an intent associated with the user to purchase the product;

generate, based on the intent associated with the user to purchase the product, a catalog that includes a plurality of products that match the request by the user to purchase the product by training, based on historical data, a convolution neural network (CNN) with a long short-term memory (LSTM) layer machine learning classifier;

receive selection of a product from the plurality of products;

receive identification of a quantity associated with the selected product;

determine, based on the received selection of the product from the plurality of products and the received identification of the quantity associated with the selected product, whether sufficient funds are available for purchase of the selected product;

based on a determination that sufficient funds are available for purchase of the selected product, generate a purchase request;

generate, based on the purchase request, a purchase order associated with the selected product; and

procure, based on the purchase order associated with the selected product, the selected product for the user.

17. The non-transitory computer readable medium according to claim 16 , wherein the machine readable instructions to generate, based on the analysis of the request by the user to purchase the product and the attribute associated with the user, the intent associated with the user to purchase the product, and generate, based on the intent associated with the user to purchase the product, the catalog that includes the plurality of products that match the request by the user to purchase the product, when executed by the at least one hardware processor, further cause the at least one hardware processor to:

generate, based on the analysis of the request by the user to purchase the product and the attribute associated with the user using the trained machine learning classifier, the intent associated with the user to purchase the product; and

generate, based on an analysis of the intent associated with the user to purchase the product using the trained machine learning classifier, the catalog that includes the plurality of products that match the request by the user to purchase the product.

18. The non-transitory computer readable medium according to claim 16 , wherein the machine readable instructions to ascertain, based on the chat conducted with the conversational chatbot, the request by the user to purchase the product, when executed by the at least one hardware processor, further cause the at least one hardware processor to:

convert, for the chat conducted with the conversational chatbot, a speech input to text or a text input to speech, to ascertain the request by the user to purchase the product.

19. The non-transitory computer readable medium according to claim 16 , wherein the machine readable instructions, when executed by the at least one hardware processor, further cause the at least one hardware processor to:

ascertain, based on a further chat conducted with the conversational chatbot to request a user profile associated with the user, user profile details of the user profile associated with the user.