DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office Action is in response to the communication filed on 10 October 2025.
Claims 1-21 are being considered on the merits.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-21 are rejected under 35 USC § 101
Claim 1:
Step 1: Independent claim 1 recites a non-transitory computer readable medium and therefore falls under one of the four statutory categories of patent-eligible subject matter.
Step 2A Prong 1:
Analyzing the acquired data to generate a first set of labels; (Mental Process: Analyzing data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can evaluate data entirely in their minds or with the assistance of a pen and paper.)
Converting the acquired data to feature vectors by generating embeddings for the acquired data; (Mental Process: Converting data into vectors by generating embeddings is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can produce (i.e. generate) representations of data in the form of a vector (i.e. any quantity that has magnitude and direction) entirely in their mind or with a pen and paper.)
Generating a second set of labels for the feature vectors through a multi-stage pipeline based on the extracted events, (Mental Process: Generating a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can evaluate feature vectors and conceive of a set of labels entirely in their minds or with the assistance of a pen and paper.)
normalizing, with the transformer, the acquired data to a uniform format (Mental process: normalizing data process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a “processor”, nothing in this claim element precludes the step from practically being performed in the mind or with the assistance of a pen and paper. A person can take data and apply an algorithm or rules to the data to normalize and manipulate the data into a uniform format).
connecting, with the transformer, the normalized data, wherein the transformer stores the connected data in a database (Mental process: connecting normalized data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a “transformer”, nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take data written on a piece of paper and connect the data by drawing a line between data points).
classifying, using a classifier model, the extracted events based on at least one of the first set of labels or the second set of labels; (Mental process: Classifying events by adding labels from a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at a list of events and possible labels and classify the events to the label in their mind or on a piece of paper. Examiner notes that the broadest reasonable interpretation of “a classifier model” means a classification system.)
projecting the extracted events to the acquired data to generate a relational table, wherein records of the relational table include the extracted events and one or more slices of the acquired data; (Mental process: projecting events to data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take events and present them in the context of the data).
Projecting the second set of labels to the one or more slices based on the extracted events; (Mental process: projecting labels to data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take labels and present them over events in the context of the data).
Connecting data from one or more sources in a relational table by determining, based on a configuration file, one or more joins or aggregations to perform on the data; and (Mental process: connecting data by determining joins or aggregations is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a “configuration file”, nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at data in a relational table, a configuration table, and determine aggregations on data to connect them).
generating the one or more customized insights from the relational table of the extracted events representing user interactions based on the second set of labels (Mental process: Generating customized insights based on a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at user interactions (i.e. events) and come up with (i.e. generate) insights about that interaction based on a given list of labels).
Step 2A Prong 2: This judicial exception is not integrated into practical application
A non-transitory computer readable medium including instructions that are executable by one or more processors to cause a system to perform a method for customized insights, the method comprising (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
receive a request for one or more customized insights; (insignificant extra-solution activity to the judicial exception: storing and retrieving data from memory – See MPEP § 2106.05(g))
acquiring data, through API calls from one or more sources selected based on the requested one or more customized insights, wherein the one or more sources format and organize data differently (insignificant extra-solution activity to the judicial exception: Receiving or transmitting data over a network – See MPEP § 2106.05(g)).
extracting with a transformer, from the acquired data, events that each represent an interaction between a user and a healthcare service; ((insignificant extra-solution activity to the judicial exception: storing and retrieving data from memory – See MPEP § 2106.05(g))
Wherein the multi-stage pipeline comprises a plurality of machine learning models such that an output of a first model of the plurality of models is an input to a second model of the plurality of models; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
wherein the classifier model is trained on the connected data stored in the database (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
A non-transitory computer readable medium including instructions that are executable by one or more processors to cause a system to perform a method for customized insights, the method comprising (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
receive a request for one or more customized insights; (Insignificant Extra Solution Activity: storing and retrieving data from memory is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d)))
acquiring data, through API calls from one or more sources selected based on the requested one or more customized insights, wherein the one or more sources format and organize data differently (Insignificant Extra Solution Activity: Receiving or transmitting data over a network is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d))
extracting with a transformer, from the acquired data, events that each represent an interaction between a user and a healthcare service; (Insignificant Extra Solution Activity: storing and retrieving data from memory is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d))
Wherein the multi-stage pipeline comprises a plurality of machine learning models such that an output of a first model of the plurality of models is an input to a second model of the plurality of models; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
wherein the classifier model is trained on the connected data stored in the database (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Claim 2:
Step 2a Prong 1: See the rejection of claim 1 above. The same rationale applies to this dependent claim
determining the second set of labels to associate with the acquired data using machine learning models based on the one or more annotations, wherein the second set of labels indicate one or more intentions of the user and one or more actions of a service provider of the healthcare service. (Mental process: Determining a set of labels to associate with acquired data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at a pre-populated list of data (i.e. acquired) and determine what set of labels to associate with the data in their mind or by writing it down on the list).
Step 2A Prong 2: This judicial exception is not integrated into practical application
receiving, for the acquired data, one or more annotations that are defined using a configuration file and that indicate an event of the events in the data (insignificant extra-solution activity to the judicial exception: Receiving or transmitting data over a network – See MPEP § 2106.05(g)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
receiving, for the acquired data, one or more annotations that are defined using a configuration file and that indicate an event of the events in the data (Insignificant Extra Solution Activity: Receiving or transmitting data over a network is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d)).
Claim 3:
Step 2A Prong 1: See the rejection of claim 2 above. The same rationale applies to this dependent claim
the second set of labels indicate the extracted events using one or more mappings between the one or more intentions and the one or more actions (Mental process: Determining tags (using mappings between intentions and actions) to associate with acquired data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at a pre-populated list of data (i.e. acquired) and determine what tags (relating to intentions and actions) to place on the data in their mind or by writing it down on the list).
Step 2A Prong 2 and Step 2B: The claim does not include additional elements.
Claim 4:
Step 2A Prong 1: See the rejection of claim 3 above. The same rationale applies to this dependent claim
one or more mappings between the one or more intentions and the one or more actions is determined using a multi-label multi-class classification model (Mental process: Determining tags (using mappings between intentions and actions and using a multi-label, multi-class model) to associate with acquired data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at a pre-populated list of data (i.e. acquired), create a model that uses more than one label and class and determine what tags (relating to intentions and actions) to place on the data in their mind or by writing it down on the list).
Step 2A Prong 2 and Step 2B: The claim does not include additional elements.
Claim 5:
Step 2A Prong 1: See the rejection of claim 3 above. The same rationale applies to this dependent claim
Step 2A Prong 2: This judicial exception is not integrated into practical application
a machine learning model of the machine learning models is trained using the one or more mappings between the one or more intentions and the one or more actions (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
a machine learning model of the machine learning models is trained using the one or more mappings between the one or more intentions and the one or more actions (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Claim 6:
Step 2A Prong 1: See the rejection of claim 5 above. The same rationale applies to this dependent claim.
determining one or more recommendation actions based on the determined intent of the communication, wherein the one or more recommendations are generated by a multi-label classifier; (Mental process: Determining recommendation actions based on the intent of a communication is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at the intent of the communication and figure out (i.e. determine) recommendation actions where that person can be a classifier).
generating one or more responses associated with the one or more recommendation actions (Mental process: Generating responses associated with recommendation actions is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at recommendation actions and draft a response (generate) associated with the recommendation).
Step 2A Prong 2: This judicial exception is not integrated into practical application
receiving a communication from a user (insignificant extra-solution activity to the judicial exception: Receiving or transmitting data over a network – See MPEP § 2106.05(g)).
determining intent of the communication using the trained machine learning model (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f)).
presenting the one or more responses in a consumable format (insignificant extra-solution activity to the judicial exception: Presenting offers and gathering statistics – See MPEP § 2106.05(g)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
receiving a communication from a user (Insignificant Extra Solution Activity: Receiving or transmitting data over a network is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d))).
determining intent of the communication using the trained machine learning model (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f)).
presenting the one or more response communications in a consumable format (Insignificant Extra Solution Activity: Presenting offers and gathering statistics is well-understood, routine, conventional activity – see Berkheimer evidence from MPEP 2106.05(d))
Claim 7:
Step 2A Prong 1: See the rejection of claim 6 above. The same rationale applies to this dependent claim
Step 2A Prong 2: This judicial exception is not integrated into practical application
the received communication is at least one of: an email, a chat message, or a phone call; (insignificant extra-solution activity to the judicial exception: Receiving or transmitting data over a network – See MPEP § 2106.05(g)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
the received communication is at least one of: an email, a chat message, or a phone call; (Insignificant Extra Solution Activity: Receiving or transmitting data over a network is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d))
Claim 8:
Step 2A Prong 1: See the rejection of claim 2 above. The same rationale applies to this dependent claim
determining the second set of labels to associate with the data using machine learning models includes generating a hierarchy of the second set of labels. (Mental process: Generating a hierarchy is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “machine learning models”, nothing in this claim element precludes the step from practically being performed in the mind or with a pen and paper. For example, a person can take the the second set of labels and create a hierarchy based on any criteria).
Step 2A Prong 2 and Step 2B: The claim does not include additional elements.
Claim 9:
Step 2A Prong 1: See the rejection of claim 2 above. The same rationale applies to this dependent claim
projecting the extracted events to the acquired data to generate a relational table further comprises generating one or more slices of the acquired data (Mental process: generating slices of acquired data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can create slices of data by taking data and partitioning it their minds or on paper).
Step 2A Prong 2: This judicial exception is not integrated into practical application
projecting the one or more slices of the acquired data to the second set of labels representing the extracted events. (insignificant extra-solution activity to the judicial exception: Presenting offers and gathering statistics – See MPEP § 2106.05(g)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
projecting the one or more slices of the acquired data to the second set of labels representing the extracted events. (Insignificant Extra Solution Activity: Presenting offers and gathering statistics is well-understood, routine, conventional activity – see Berkheimer evidence from MPEP 2106.05(d)).
Claim 10:
Step 2A Prong 1: See the rejection of claim 9 above. The same rationale applies to this dependent claim
projecting the one or more slices of the acquired data to the second set of labels representing the extracted events further comprises generating the relational table to include the one or more slices of the acquired data as one or more records; (Mental process: Generating a table that includes slices of data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can draw a table that includes data).
including the one or more slices of the acquired data as field of the one or more records (Mental process: Generating a table that includes slices of data that is specifically a field of the table is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can draw a table that includes data as a field in the table).
including additional information as additional fields of the one or more records (Mental process: Generating a table that includes slices of data that includes additional information is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can draw a table that includes additional information).
Step 2A Prong 2 and Step 2B: The claim does not include additional elements.
Claim 11:
Step 2A Prong 1: See the rejection of claim 1 above. The same rationale applies to this dependent claim
classifying, using a classifier model, the acquired data further comprises grouping the one or more labels to a core topic, wherein the core topic indicates a communication intent of the user (Mental process: Classifying data by grouping labels to a topic is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than a “classifier model”, nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can have group labeled data according to topics based on the intent of the user).
Step 2A Prong 2 and Step 2B: The claim does not include additional elements.
Claim 12:
Step 2a Prong 1: See the rejection of claim 1 above. The same rationale applies to this dependent claim
generating the one or more customized insights from the relational table of the extracted events representing user interactions is based on the machine learning models selected from a machine learning models repository using a configuration file (Mental process: Generating customized is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “machine learning models” and “a configuration file”, nothing in this claim element precludes the step from practically being performed in the mind. For example, a person look at events and mentally determine (i.e. generate) insights based on the events).
Step 2A Prong 2 and Step 2B: The claim does not include additional elements.
Claim 13:
Step 1: Independent claim 13 recites a method and therefore falls under one of the four statutory categories of patent-eligible subject matter.
Step 2A Prong 1:
Analyzing the acquired data to generate a first set of labels; (Mental Process: Analyzing data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can evaluate data entirely in their minds or with the assistance of a pen and paper.)
Converting the acquired data to feature vectors by generating embeddings for the acquired data; (Mental Process: Converting data into vectors by generating embeddings is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can produce (i.e. generate) representations of data in the form of a vector (i.e. any quantity that has magnitude and direction) entirely in their mind or with a pen and paper.)
Generating a second set of labels for the feature vectors through a multi-stage pipeline based on the extracted events; (Mental Process: Generating a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can evaluate feature vectors and conceive of a set of labels entirely in their minds or with the assistance of a pen and paper.)
normalizing, with the transformer, the acquired data to a uniform format (Mental process: normalizing data process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a “processor”, nothing in this claim element precludes the step from practically being performed in the mind or with the assistance of a pen and paper. A person can take data and apply an algorithm or rules to the data to normalize and manipulate the data into a uniform format).
connecting, with the transformer, the normalized data, wherein the transformer stores the connected data in a database (Mental process: connecting normalized data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a “transformer”, nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take data written on a piece of paper and connect the data by drawing a line between data points).
classifying, using a classifier model, the extracted events based on at least one of the first set of labels or the second set of labels (Mental process: Classifying events by adding labels from a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at a list of events and possible labels and classify the events to the label in their mind or on a piece of paper. Examiner notes that the broadest reasonable interpretation of “a classifier model” means a classification system.)
classifying, using a classifier model, the extracted events based on at least one of the first set of labels or the second set of labels (Mental process: Classifying events by adding labels from a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at a list of events and possible labels and classify the events to the label in their mind or on a piece of paper. Examiner notes that the broadest reasonable interpretation of “a classifier model” means a classification system.)
projecting the extracted events to the acquired data to generate a relational table, wherein records of the relational table include the extracted events and one or more slices of the acquired data (Mental process: projecting events to data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take events and present them in the context of the data).
Projecting the second set of labels to the one or more slices based on the extracted events; (Mental process: projecting labels to data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take labels and present them over events in the context of the data).
Connecting data from one or more sources in a relational table by determining, based on a configuration file, one or more joins or aggregations to perform on the data; and (Mental process: connecting data by determining joins or aggregations is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a “configuration file”, nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at data in a relational table, a configuration table, and determine aggregations on data to connect them).
generating the one or more the customized insights from the relational table of the extracted events representing user interactions based on the second set of labels (Mental process: Generating customized insights based on a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at user interactions (i.e. events) and come up with (i.e. generate) insights about that interaction based on a given list of labels).
Step 2A Prong 2: This judicial exception is not integrated into practical application
receiving a request for one or more customized insights (Insignificant Extra Solution Activity: Receiving or transmitting data from memory – see MPEP 2106.05(g))
extracting with a transformer, from the acquired data, events that each represent an interaction between a user and a healthcare service (insignificant extra-solution activity to the judicial exception: storing and retrieving data from memory – See MPEP § 2106.05(g))
Wherein the multi-stage pipeline comprises a plurality of machine learning models such that an output of a first model of the plurality of models is an input to a second model of the plurality of models; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
wherein the classifier model is trained on the connected data stored in the database (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
receiving a request for one or more customized insights ((Insignificant Extra Solution Activity: storing and retrieving data from memory is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d))
extracting with a transformer, from the acquired data, events that each represent an interaction between a user and a healthcare service; (Insignificant Extra Solution Activity: storing and retrieving data from memory is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d))
acquiring data through API calls from one or more sources selected based on the requested one or more customized insights wherein the one or more sources format and organize data differently (Insignificant Extra Solution Activity: Receiving or transmitting data over a network is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d)).
Wherein the multi-stage pipeline comprises a plurality of machine learning models such that an output of a first model of the plurality of models is an input to a second model of the plurality of models; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
wherein the classifier model is trained on the connected data stored in the database (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Claim 14:
Step 2A Prong 1: See the rejection of claim 13 above. The same rationale applies to this dependent claim
determining the second set of labels to associate with the acquired data using machine learning models based on the one or more annotations, wherein the second set of labels indicate one or more intentions of a user and one or more actions of a service provider, (Mental process: Determining a set of labels to associate with acquired data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at a pre-populated list of data (i.e. acquired) and determine what set of labels to associate with the data in their mind or by writing it down on the list).
Step 2A Prong 2: This judicial exception is not integrated into practical application
extracting, from the acquired data, events further comprises receiving, for the acquired data, one or more annotations that are defined using a configuration file and that indicate an event of the events in the data (insignificant extra-solution activity to the judicial exception: Receiving or transmitting data over a network – See MPEP § 2106.05(g))
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
extracting, from the acquired data, events further comprises receiving, for the acquired data, one or more annotations that are defined using a configuration file and that indicate an event of the events in the data (Insignificant Extra Solution Activity: Receiving or transmitting data over a network is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d))
Claim 15:
Step 2A Prong 1: See the rejection of claim 14 above. The same rationale applies to this dependent claim
the second set of labels indicate the extracted events using one or more mappings between the one or more intentions and the one or more actions (Mental process: Determining tags (using mappings between intentions and actions) to associate with acquired data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at a pre-populated list of data (i.e. acquired) and determine what tags (relating to intentions and actions) to place on the data in their mind or by writing it down on the list).
Step 2A Prong 2 and Step 2B: The claim does not include additional elements.
Claim 16:
Step 2A Prong 1: See the rejection of claim 15 above. The same rationale applies to this dependent claim
Step 2A Prong 2: This judicial exception is not integrated into practical application
a machine learning model of the machine learning models is trained using the one or more mappings between the one or more intentions and the one or more actions (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
a machine learning model of the machine learning models is trained using the one or more mappings between the one or more intentions and the one or more actions (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Claim 17:
Step 2A Prong 1: See the rejection of claim 16 above. The same rationale applies to this dependent claim
determining one or more recommendation actions based on the determined intent of the communication, wherein the one or more recommendations are generated by a multi-label classifier; (Mental process: Determining recommendation actions based on the intent of a communication is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at the intent of the communication and figure out (i.e. determine) recommendation actions where that person can be a classifier).
generating one or more responses associated with the one or more recommendation actions (Mental process: Generating responses associated with recommendation actions is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at recommendation actions and draft a response (generate) associated with the recommendation).
Step 2A Prong 2: This judicial exception is not integrated into practical application
receiving a communication from a user (insignificant extra-solution activity to the judicial exception: Receiving or transmitting data over a network – See MPEP § 2106.05(g)).
determining intent of the communication using the trained machine learning model (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f)).
presenting the one or more responses in a consumable format (insignificant extra-solution activity to the judicial exception: Presenting offers and gathering statistics – See MPEP § 2106.05(g)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
receiving a communication from a user (Insignificant Extra Solution Activity: Receiving or transmitting data over a network is well-understood, routine, conventional activity – see Berkheimer evidence MPEP § 2106.05(d))).
determining intent of the communication using the trained machine learning model (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f)).
presenting the one or more responses in a consumable format (Insignificant Extra Solution Activity: Presenting offers and gathering statistics is well-understood, routine, conventional activity – see Berkheimer evidence from MPEP 2106.05(d))
Claim 18:
Step 2A Prong 1: See the rejection of claim 14 above. The same rationale applies to this dependent claim
projecting the extracted events to the acquired data to generate a relational table further comprises generating the one or more slices of the acquired data (Mental process: projecting data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can present (i.e. project) data by decomposing the data (i.e. into slices) in their minds or on paper).
projecting the one or more slices of the acquired data to the second set of labels representing the extracted events (Mental process: projecting labels to data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take labels and present them over events in the context of the data).
Step 2A Prong 2 and Step 2B: The claim does not include additional elements.
Claim 19:
Step 2A Prong 1: See the rejection of claim 18 above. The same rationale applies to this dependent claim
projecting the one or more slices of the acquired data to the second set of labels representing the extracted data further comprises generating the relational table to include the one or more slices of the acquired data as one or more records (Mental process: Generating a table that includes slices of data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can draw a table that includes data).
including the one or more slices of the acquired data as field of the one or more records (Mental process: Generating a table that includes slices of data that is specifically a field of the table is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can draw a table that includes data as a field in the table).
including additional information as additional fields of the one or more records. (Mental process: Generating a table that includes slices of data that includes additional information is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can draw a table that includes additional information).
Step 2A Prong 2 and Step 2B: The claim does not include additional elements.
Claim 20:
Step 1: Independent claim 1 recites a system and therefore falls under one of the four statutory categories of patent-eligible subject matter.
Step 2A Prong 1:
Analyzing the acquired data to generate a first set of labels; (Mental Process: Analyzing data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can evaluate data entirely in their minds or with the assistance of a pen and paper.)
Converting the acquired data to feature vectors by generating embeddings for the acquired data; (Mental Process: Converting data into vectors by generating embeddings is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can produce (i.e. generate) representations of data in the form of a vector (i.e. any quantity that has magnitude and direction) entirely in their mind or with a pen and paper.)
Generating a second set of labels for the feature vectors through a multi-stage pipeline based on the extracted events; (Mental Process: Generating a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can evaluate feature vectors and conceive of a set of labels entirely in their minds or with the assistance of a pen and paper.)
normalizing, with the transformer, the acquired data to a uniform format (Mental process: normalizing data process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a “processor”, nothing in this claim element precludes the step from practically being performed in the mind or with the assistance of a pen and paper. A person can take data and apply an algorithm or rules to the data to normalize and manipulate the data into a uniform format).
connecting, with the transformer, the normalized data, wherein the transformer stores the connected data in a database (Mental process: connecting normalized data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a “transformer”, nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take data written on a piece of paper and connect the data by drawing a line between data points).
classifying, using a classifier model, the extracted events based on at least one of the first set of labels or the second set of labels; (Mental process: Classifying events by adding labels from a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at a list of events and possible labels and classify the events to the label in their mind or on a piece of paper. Examiner notes that the broadest reasonable interpretation of “a classifier model” means a classification system.)
projecting the extracted events to the acquired data to generate a relational table, wherein records of the relational table include the extracted events and one or more slices of the acquired data; (Mental process: projecting events to data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take events and present them in the context of the data).
Projecting the second set of labels to the one or more slices based on the extracted events; (Mental process: projecting labels to data is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can take labels and present them over events in the context of the data).
Connecting data from one or more sources in a relational table by determining, based on a configuration file, one or more joins or aggregations to perform on the data; and (Mental process: connecting data by determining joins or aggregations is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a “configuration file”, nothing in this claim element precludes the step from practically being performed in the mind. For example, a person can look at data in a relational table, a configuration table, and determine aggregations on data to connect them).
generating the one or more customized insights from the relational table of the extracted events representing user interactions based on the second set of labels (Mental process: Generating customized insights based on a set of labels is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind; nothing in this cla