DETAILED ACTION
Status of Claims
This communication is in response to applicant response filed on 06/01/2026.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1 and 11 are amended. Claims 6, 8-9, 16, and 18-19 are cancelled. Claims 1-5, 7, 10-15, 17 and 20 are currently pending and have been examined.
Continued Prosecution Application
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/18/2026 has been entered.
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 1-5, 7, 10-15, 17 and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-5, 7, and 10 are drawn to a method which is within the four statutory categories (i.e., a process). Claims 11-15, 17, and 20 are drawn to a system which is within the four statutory categories (i.e. a machine).
Since the claims are directed toward statutory categories, it must be determined if the claims are directed towards a judicial exception (i.e. a law of nature, a natural phenomenon, or an abstract idea). Based upon consideration of all of the relevant factors with respect to the claim as a whole, Claims 1-5, 7, 10-15, 17 and 20 are determined to be directed to an abstract idea. The rationale for this determination is explained below:
Independent claims 1 and 11 as a whole directed toward an abstract idea of procuring goods or services (i.e. Receiving client interaction data from multiple sources, generating a profile for each client using the data, generating an interaction value score for client interactions (using a machine learning algorithm), identifying and removing “false positive” client interactions, providing the processed interactions and scores to a customer relationship management (CRM) program) These fall within the examples of abstract ideas (managing client relationships and analyzing interactions) which falls under abstract idea bucket of Certain Methods of Organizing Human Activities.
Because the claim recites abstract ideas, the analysis proceeds to determine whether the claim recites additional elements that recite a practical application of the abstract ideas. According to MPEP 2106.04(d), additional elements that recite an instruction to apply the abstract ideas using computing systems and electronic device and using machine learning algorithm, that recite that generally link the use of the abstract ideas to a particular technological environment or field of use are not indicative of a practical application. Here, the additional elements of the electronic device (BRI of which is general purpose computer) fail to recite a practical application because they are instructions to apply the abstract ideas using computers. The claim merely implements this abstract idea on a generic computer program executed by a backend electronic device. There is no indication that the claimed invention improves the functioning of a computer or another technology.The steps (receiving, generating, identifying, discounting, removing, providing) are performed by conventional computing components and do not effect an improvement in computer functionality or another technical field.
Therefore, the claim as a whole fails to recite a practical application of the abstract ideas.
The dependent claims 2-5, 7, 10, 12-15, 17 and 20 merely further define the abstract idea and are, therefore, directed to an abstract idea for similar reasons as given above. Therefore, the claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Allowable Subject Matter Over Prior Art
The prior arts of record does not teach or suggest out-of-office reply and assistant interaction as taught by the claims, a combination of profile elements, and profile generation as claimed, among other features of the independent claims. Upon further searching various databases claims as whole appears to be non- obvious combination of limitations.
Response to Arguments
As to the remark, Applicant asserted that: Under Step 2A, Prong One of the Alice/Mayo framework, the amended claims are not properly characterized as merely "procuring goods or services," "organizing information," or "creating and managing records." The claims are directed to automated silent inference of client/customer interaction using a particular electronic data-processing pipeline. The claimed invention addresses a technological problem arising from fragmented electronic interaction data and manual CRM entry, namely that interaction information from calendar systems, email systems, videoconferencing systems, telephone logs, and chat/messaging systems is not reliably and accurately captured in CRM systems without further computer- implemented inference, filtering, scoring, and profile generation. The amended claims therefore recite more than the result of customer relationship management; they recite a particular sequence of computer operations for transforming heterogeneous electronic interaction data into filtered, scored, profile-associated CRM records.
Under Step 2A, Prong Two, even if some aspect of the claims were considered to involve an abstract idea, the amended claims integrate any such idea into a practical application. The claimed computer program does not merely receive data and display a result. Instead, the amended claims require metadata-based profile generation, removal of defined false-positive interactions from the pool of interactions that are further considered, metadata-driven machine-learning scoring of remaining interactions, and structured ingestion by a CRM computer system. This arrangement improves the accuracy and usefulness of electronically generated CRM interaction data by preventing out-of-office replies and assistant interactions from being treated as meaningful client/customer interactions and by scoring interactions using electronically captured metadata that would not be available from a generic manual record-keeping process. The Examiner stated that the claims invoked a trained machine learning algorithm and generic modules on a backend device but did not recite how the algorithm or system is implemented in a way that improves computer functioning. The amended claims directly address that concern. The trained machine learning algorithm is now recited as operating within a more specific ordered pipeline and as generating interaction value scores based on particular electronic interaction metadata, including whether cameras were turned on during a virtual meeting, meeting length, number of emails in a chain, number of email participants, speed of response, and sentiment. In addition, the claims now recite that false-positive interactions are removed from the pool of interactions further considered before the interaction records are provided for CRM ingestion. These limitations define how the computer program processes the electronic data to produce improved CRM interaction records, rather than merely stating an abstract business result.
Examiner would like to point out to applicant that the claims as currently drafted remain directed to data collection, organization, analysis, and output—activities that courts have found to be abstract ideas under Step 2A, Prong One of the Alice/Mayo framework (see, e.g., Electric Power Group v. Alstom, 830 F.3d 1350 (Fed. Cir. 2016); SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161 (Fed. Cir. 2018)). While the claims do recite a sequence of operations (including profile generation, false-positive identification, filtering, scoring, and data provision), these steps are performed by a generic computer program and do not effect an improvement to the functioning of the computer itself or to another technology or technical field. The technological problem identified—fragmented interaction data and the need for accurate CRM entry—relates to business data integration and management, not to a technical improvement in computer processing. The recited “electronic data-processing pipeline” and use of a “trained machine learning algorithm” are described at a high level of generality, without details as to how the claimed invention improves computer technology or performs data processing in a manner different from conventional techniques. The claims do not specify a novel machine learning technique, a new data structure, or an improvement to data storage or retrieval at the technical level. Accordingly, the claims are still properly characterized as being directed to the abstract idea of collecting, analyzing, and managing business information.
The recitation of a machine learning algorithm operating on specific types of metadata (e.g., camera status, meeting length, sentiment) does not constitute an improvement to the functioning of the computer itself, nor does it provide a technical solution to a technical problem. The claim language does not describe a novel machine learning technique, a new data structure, or a non-conventional way of processing data that would integrate the abstract idea into a practical application.
The additional claim elements, even when considered as an ordered combination, do not amount to significantly more than the abstract idea itself. The rejection under 35 U.S.C. § 101 is therefore maintained.
Conclusion
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/NEHA PATEL/Supervisory Patent Examiner, Art Unit 3699
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