Cognitive platform for autonomous data orchestration and the method thereof

1 . A cognitive platform, comprising:

at least one processor;

a cognitive computing engine; and

at least one memory unit operatively coupled to the at least one processor, having instructions stored thereon that, when executed by the at least one processor, cause the at least one processor to:

generate, by the cognitive computing engine, at least one digital event, wherein the at least one digital event is generated based on at least one of previous activity or inactivity of one or more entities communicatively coupled to the cognitive platform;

access, by the cognitive computing engine, data from a central intelligence store based on the generated at least one digital event, wherein the data comprises context information, state information, and a plurality of previous digital events stored in the central intelligence store;

determine, by the cognitive computing engine, an intent of the generated at least one digital event based on the data accessed from the central intelligence store, wherein:

the intent is a function of the context information, the state information, and the plurality of previous digital events, and

the cognitive computing engine is configured to learn from the at least one generated event via one or more machine learning (ML) models configured to automatically update based on the data accessed from the central intelligence store;

identify, by the cognitive computing engine, at least one target entity based on the determined intent;

compose, by the cognitive computing engine, a data package for the identified at least one target entity;

transform, by the cognitive computing engine, the data package to a natural language text, wherein the transformed data package comprises a Uniform Resource Locator (URL) link to point to a proposed action intended for the identified at least one target entity;

communicate, by the cognitive computing engine, the transformed data package to the identified at least one target entity; and

update, by the cognitive computing engine, the central intelligence store with the generated at least one digital event and the determined intent for subsequent digital events.

2 . The cognitive platform of claim 1 , wherein the at least one target entity is further identified based on the data accessed from the central intelligence store.

3 . The cognitive platform of claim 1 , wherein the identified at least one target entity is one or more external computing devices communicatively coupled to the cognitive computing engine over a computer network.

4 . The cognitive platform of claim 1 , wherein the data package is composed based on the determined intent, the data received from the central intelligence store, and relationship data from a mindmap.

5 . A computer implemented method for a cognitive platform, comprising:

generating, by a cognitive computing engine, at least one digital event, wherein the at least one digital event is generated based on at least one of previous activity or inactivity of one or more entities communicatively coupled to the cognitive platform;

accessing, by the cognitive computing engine, data from a central intelligence store based on the generated at least one digital event, wherein the data comprises context information, state information, and a plurality of previous digital events stored in the central intelligence store;

determining, by the cognitive computing engine, an intent of the generated at least one digital event based on-the data accessed from the central intelligence store, wherein:

the intent is a function of the context information, the state information, and the plurality of previous digital events, and;

the cognitive computing engine is configured to learn from the generated at least one digital event via one or more machine learning (ML) models configured to automatically update based on the data accessed from the central intelligence store;

identifying, by the cognitive computing engine, at least one target entity based on the determined intent;

composing, by the cognitive computing engine, a data package for the identified at least one target entity;

transforming, by the cognitive computing engine, the data package to a natural language text, wherein the transformed data package comprises a Uniform Resource Locator (URL) link to point to a proposed action intended for the identified at least one target entity;

communicating, by the cognitive computing engine, the transformed data package to the identified at least one target entity; and

updating, by the cognitive computing engine, the central intelligence store, with the generated at least one digital event and the determined intent for subsequent digital events.

6 . The computer implemented method of claim 5 , wherein the at least one target entity is further identified based on the data accessed from the central intelligence store.

7 . The computer implemented method of claim 5 , wherein the identified at least one target entity is one or more external computing devices communicatively coupled to the cognitive computing engine over a computer network.

8 . The computer implemented method of claim 5 , wherein the data package is composed based on the determined intent, the data received from the central intelligence store and, relationship data from a mindmap.

9 . A non-transitory computer readable medium having stored thereon instructions, comprising machine executable code which when executed by at least one processor, causes the at least one processor to perform steps comprising:

generate at least one digital event, wherein the at least one digital event is generated based on at least one of previous activity or inactivity of one or more entities communicatively coupled to a cognitive platform;

access data from a central intelligence store based on the generated at least one digital event, wherein the data comprises context information, state information, and a plurality of previous digital events stored in the central intelligence store;

determine an intent of the generated at least one digital event via one or more machine learning (ML) models configured to automatically update based on the data accessed from the central intelligence store, wherein the intent is a function of the context information, the state information, and the plurality of previous digital events;

identify at least one target entity based on the determined intent;

compose a data package for the identified at least one target entity;

transform the data package to a natural language text, wherein the transformed data package comprises a Uniform Resource Locator (URL) link to point to a proposed action intended for the identified at least one target entity;

communicate the transformed data package to the identified at least one target entity; and

update the central intelligence store with the generated at least one digital event and the determined intent for subsequent digital events.

10 . The non-transitory computer readable medium of claim 9 , wherein the at least one target entity is further identified based on the data accessed from the central intelligence store.

11 . The non-transitory computer readable medium of claim 9 , wherein the identified at least one target entity is one or more external computing devices communicatively coupled to a cognitive computing engine over a computer network.

12 . The non-transitory computer readable medium of claim 9 , wherein the data package is composed based on the determined intent, the data received from the central intelligence store and, relationship data from a mindmap.

13 . The cognitive platform of claim 1 , wherein the at least one memory unit comprises a mindmap configured to store industry-specific ontologies, wherein the mindmap comprises a plurality of nodes representing the one or more entities and aspects associated with the one or more entities, wherein the mindmap comprises a plurality of edges representing relationship between the plurality of nodes.

14 . The cognitive platform of claim 13 , wherein the instructions when executed by the at least one processor, further cause the at least one processor to add or remove nodes and edges in the mindmap using one or more machine learning models in response to processing each generated digital event.