# US 12,120,000 B1 · Apparatus and a method for the generation of dynamic data packets > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,120,000 B1 - Document ID: US12120000B1 - Status: Granted - Kind: B1 - Application number: 18/586,977 - Filed: 2024-02-26 - Granted: 2024-10-15 - Earliest claimed: 2024-02-26 - Applicants: The Strategic Coach Inc. - Inventors: Barbara Sue Smith; Daniel J. Sullivan - Web page: https://patentgrep.com/patent/US12120000B1 ## CPC - H04L 41/16: using machine learning or artificial intelligence - H04L 9/32: including means for verifying the identity or authority of a user of the system {or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials} - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract An apparatus for the generation of dynamic data packets is disclosed. The apparatus includes at least processor and a memory communicatively connected to the processor. The memory instructs the processor to receive a plurality of entity profiles comprising a plurality of attribute data. The processor identifies target data for each entity profile using the attribute data The memory instructs the processor to pair a first entity profile and a second entity profile of the plurality of entity profiles as a function of the assignment. The memory instructs the processor to generate a first dynamic data packet as function of the pairing of the entity profile and the second entity profile. The memory instructs the processor to assign the first dynamic data packet to a first event handler. The memory instructs the processor to display the first dynamic data packet using a dynamic content transmitter on a display device. ## Claims ### Claim 1 An apparatus for the generation of dynamic data packets, wherein the apparatus comprises: at least a processor; and a memory communicatively connected to the at least a processor, wherein the memory containing instructions configuring the at least a processor to: receive a plurality of entity profiles comprising a plurality of attribute data; identify target data for each entity profile of the plurality of entity profiles as function of the attribute data; pair a first entity profile and a second entity profile of the plurality of entity profiles as a function of the target data, wherein pairing the first entity profile and the second entity profile comprises: iteratively training an entity profile machine-learning model using entity profile training data, wherein the entity profile training data comprises a plurality of target data and entity profiles as inputs correlated to examples of pairings of entity profiles as outputs; and pairing the first entity profile and the second entity profile using the trained entity profile machine-learning model; assign two or more tools to the first entity profile and the second entity profile as a function of the target data; generate a first dynamic data packet as function of the pairing of the entity profile and the second entity profile; assign the first dynamic data packet to a first event handler; and transmit the first dynamic data packet using a dynamic content transmitter to a display device. ### Claim 2 (depends on 1) The apparatus of claim 1, wherein the memory further instructs the processor to facilitate a chatroom between the first entity profile and the second entity profile as function of a real-time text-based communication packet. ### Claim 3 (depends on 1) The apparatus of claim 1, wherein the memory further instructs the processor to facilitate a video call between the first entity profile and the second entity profile as function of a real-time video communication packet. ### Claim 4 (depends on 1) The apparatus of claim 1, wherein identifying target data for each entity profile of the plurality of entity profiles further comprises identifying a performance metric for each profile of the plurality of entity profiles, wherein the performance metric comprises a time component associated with a target. ### Claim 5 (depends on 1) The apparatus of claim 1, wherein the memory further instructions the processor to encrypt the first dynamic data packet using an encryption process. ### Claim 6 (depends on 1) The apparatus of claim 1, wherein at least one of the two or more tools comprises a goal setting tool. ### Claim 7 (depends on 1) The apparatus of claim 1, wherein at least one of the two or more tools comprises a time management tool. ### Claim 8 (depends on 1) The apparatus of claim 1, wherein at least one of the two or more tools comprises a resource management tool. ### Claim 9 (depends on 1) The apparatus of claim 1, wherein paring the first entity profile and the second entity profile comprises paring the first entity profile and the second entity profile as a function of a mentorship collaboration criteria. ### Claim 10 (depends on 1) The apparatus of claim 1, wherein paring the first entity profile and the second entity profile comprises paring the first entity profile and the second entity profile as a function of a resource collaboration criteria. ### Claim 11 A method for the generation of dynamic data packets, wherein the method comprises: receiving, using at least a processor, a plurality of entity profiles comprising a plurality of attribute data; identifying, using the at least a processor, target data for each entity profile of the plurality of entity profiles as function of the attribute data; pairing, using the at least a processor, a first entity profile and a second entity profile of the plurality of entity profiles as a function of the target data, wherein pairing the first entity profile and the second entity profile comprises: iteratively training an entity profile machine-learning model using entity profile training data, wherein the entity profile training data comprises a plurality of target data and entity profiles as inputs correlated to examples of pairings of entity profiles as outputs; and pairing the first entity profile and the second entity profile using the trained entity profile machine-learning model; assigning, using the at least a processor, two or more tools to the first entity profile and the second entity profile as a function of the target data; generating, using the at least a processor, a first dynamic data packet as function of the pairing of the entity profile and the second entity profile; assigning, using the at least a processor, the first dynamic data packet to a first event handler; and transmitting, using the at least a processor, the first dynamic data packet using a dynamic content transmitter to a display device. ### Claim 12 (depends on 11) The method of claim 11, wherein the method further comprises facilitating, using the at least a processor, a chatroom between the first entity profile and the second entity profile as function of a real-time text-based communication packet. ### Claim 13 (depends on 11) The method of claim 11, wherein the method further comprises facilitating, using the at least a processor, a video call between the first entity profile and the second entity profile as function of a real-time video communication packet. ### Claim 14 (depends on 11) The method of claim 11, wherein identifying target data for each entity profile of the plurality of entity profiles further comprises identifying a performance metric for each profile of the plurality of entity profiles, wherein the performance metric comprises a time component associated with a target. ### Claim 15 (depends on 11) The method of claim 11, wherein the method further comprises encrypting, using the at least a processor, the first dynamic data packet using an encryption process. ### Claim 16 (depends on 11) The method of claim 11, wherein at least one of the two or more tools comprises a goal setting tool. ### Claim 17 (depends on 11) The method of claim 11, wherein at least one of the two or more tools comprises a time management tool. ### Claim 18 (depends on 11) The method of claim 11, wherein at least one of the two or more tools comprises a resource management tool. ### Claim 19 (depends on 11) The method of claim 11, wherein pairing the first entity profile and the second entity profile comprises pairing the first entity profile and the second entity profile as a function of a mentorship collaboration criteria. ### Claim 20 (depends on 11) The method of claim 11, wherein pairing the first entity profile and the second entity profile comprises pairing the first entity profile and the second entity profile as a function of a resource collaboration criteria.