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 the Claims
Claims 1-20 were previously pending. Claims 1, 8, 10-15, and 17-20 were amended in the reply filed February 23, 2026. Claims 1-20 are currently pending.
Response to Arguments
Applicant's amendments overcome the objection to the Title and it is withdrawn.
Applicant's arguments filed with respect to the rejection made under § 101 have been fully considered but they are not persuasive.
"Claims 1, 8, and 15 as amended further distinguish from Recentive by explicitly reciting the mechanism by which the machine learning module is improved. The amended limitation 'modifying, via one or more processors, training parameters for the machine learning-assisted review process based on the coding decisions by iteratively training the machine learning module in response to the coding decisions and document identifiers, wherein the training includes adjusting weights of the machine learning module based on the coding decisions and the document identifiers' recites specific steps through which the machine learning technology achieves an improvement- namely, iterative training in response to coding decisions with weight adjustment." Remarks, 11. This high-level limitation does not sufficiently distinguish the claims from those in Recentive Analytics, where the Federal Circuit held that "[t]he requirements that the machine learning model be ‘iteratively trained’ or dynamically adjusted in the Machine Learning Training patents do not represent a technological improvement" because "[i|terative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning." Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205, 1212 (Fed. Cir. 2025) (emphasis added). As discussed in the interview held January 12, 2026, Examiner recommends incorporating details regarding the elusion tests argued (see Remarks, 12-13 and published Specification ¶¶ 0047-72).
Applicant argues that the claims should be considered as whole (Remarks, 14), but this was performed. "The Examiner's characterization of the claims as merely 'collecting, analyzing, and outputting information for managing a legal document review process' oversimplifies the claims and fails to account for the specific technical requirements recited therein." Remarks, 14. This selection is from the analysis at MPEP Step 2A – Prong 1, where the claims are not considered as a whole. "Prong One asks does the claim recite an abstract idea, law of nature, or natural phenomenon?" MPEP 2106.04 II. A. 1. The claims are considered as a whole at Step 2A – Prong 2 and Step 2B.
Applicant also argues that the claims recite "significantly more" than the abstract idea. "The Examiner has not provided sufficient factual support to establish that the specific combination of elements recited by claims 1, 8, and 15 as amended—including the modification of 'training parameters for the machine learning-assisted review process based on the coding decisions by iteratively training the machine learning module in response to the coding decisions and document identifiers, wherein the training includes adjusting weights of the machine learning module based on the coding decisions and the document identifiers' tied to 'displaying an indication that the machine learning-assisted review process has reached a stopping point based on predetermined criteria'—is well-understood, routine, and conventional." Remarks, 15-16. As above, iterative training and dynamic adjustments are incidental to the nature of machine learning (i.e., they are generic features of any application of machine learning to any data environment). Moreover, determining the stopping point of the document review process is part of the abstract idea. "[T]he relevant inquiry is not whether the claimed invention as a whole is unconventional or non-routine." BSG Tech LLC v. BuySeasons, Inc., 899 F.3d 1281, 1290 (Fed. Cir. 2018). Updating an otherwise abstract algorithm to better analyze documents does not provide an inventive concept. Accordingly, the rejection is maintained.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter (abstract idea without significantly more). Claims are eligible for patent protection under § 101 if they are in one of the four statutory categories and not directed to a judicial exception to patentability. Alice Corp. v. CLS Bank Int'l, 573 U.S. 208 (2014). Claims 1-20, each considered as a whole and as an ordered combination, are directed to a judicial exception (i.e., an abstract idea) without significantly more.
MPEP 2106 Step 2A – Prong 1:
The claims recite an abstract idea reflected in the representative functions of the independent claims—including:
receiving user-defined parameters corresponding to [an] assisted review process;
retrieving a set of documents from a communication corpus based on the user-defined parameters;
displaying the set of documents thereby enabling a user to review and code the documents;
receiving a plurality of coding decisions from the user;
associating the coding decisions with the documents;
transmitting the coding decisions and document identifiers;
modifying parameters for the assisted review process based on the coding decisions in response to the coding decisions and document identifiers, and adjusting weights based on the coding decisions and the document identifiers;
storing the coding decisions in the communication corpus;
displaying an indication of the assisted review process progress; and
displaying an indication that the assisted review process has reached a stopping point based on predetermined criteria.
These limitations taken together qualify as a certain method of organizing human activities because their broadest reasonable interpretation in light of the Specification recites collecting, analyzing, and outputting information for managing a legal document review process (i.e., in the terminology of the 2019 Revised Guidance, fundamental economic practices (including mitigating risk); commercial or legal interactions (including legal obligations; business relations); managing personal behavior or relationships or interactions between people (including following rules or instructions)).
It shares similarities with other abstract ideas held to be non-statutory by the courts (see Accenture Global Services, GmbH v. Guidewire Software, 728 F.3d 1336 (Fed. Cir. 2013)—interface for generating tasks based on rules to be completed upon the occurrence of an event, similar because at another level of abstraction the claims could be characterized as an interface for generating a document review stopping point based on rules to be completed upon the occurrence of an event; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016)—receiving, screening, and distributing e-mail, similar because at another level of abstraction the claims could be characterized as receiving, screening, and coding communication documents; In re: Killian, No. 2021-2113, Fed. Cir., Aug. 23, 2022)—collecting information, understanding that information, and determining eligibility for benefits similar because at another level of abstraction the claims could be characterized as collecting information, understanding that information, and determining coding decisions of the information).
These cases describe significantly similar aspects of the claimed invention, albeit at another level of abstraction. See Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1240-41 (Fed. Cir. 2016) ("An abstract idea can generally be described at different levels of abstraction. As the Board has done, the claimed abstract idea could be described as generating menus on a computer, or generating a second menu from a first menu and sending the second menu to another location. It could be described in other ways, including, as indicated in the specification, taking orders from restaurant customers on a computer.").
MPEP 2106 Step 2A – Prong 2:
This judicial exception is not integrated into a practical application because there are no meaningful limitations that transform the exception into a patent eligible application. The elements merely serve to provide a general link to a technological environment (e.g., computers and the Internet) in which to carry out the judicial exception (computing system, computer, processors, memory having stored thereon instructions, non-transitory computer-readable medium having stored thereon instructions, training parameters for machine learning, browser-based interface, input device, machine learning module—all recited at a high level of generality).
With respect to the machine learning model in particular, the claims recite "iteratively training the machine learning module in response to the coding decisions and document identifiers, wherein the training includes adjusting weights of the machine learning module based on the coding decisions and the document identifiers." However, this is a generic aspect of any machine learning application. See Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025). In that case, similar to here, “[t]he requirements that the machine learning model be ‘iteratively trained’ or dynamically adjusted in the Machine Learning Training patents do not represent a technological improvement” because “[i|terative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning.” Id. at 1212 (emphasis added).
Although the claims have and execute instructions to perform the abstract idea itself (e.g., modules, program code, etc. to automate the abstract idea), this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." Aside from such instructions to implement the abstract idea, they are solely used for generic computer operations (e.g., receiving, storing, retrieving, transmitting data), employing the computer as a tool. See FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1096 (Fed. Cir. 2016) ("[T]he use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent-eligible subject matter.") (citing DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245,1256 (Fed. Cir. 2014)) (emphasis added). See also Recentive Analytics, Inc. v. Fox. Corp., Fed Cir. No. 2023-2437 (Apr. 18, 2025) (slip op. at 18) ("[P]atents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101.").
The claims only manipulate abstract data elements into another form. They do not set forth improvements to another technological field or the functioning of the computer itself and instead use computer elements as tools to improve the functioning of the abstract idea identified above. Looking at the additional limitations and abstract idea as an ordered combination and as a whole adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Rather than any meaningful limits, their collective functions merely provide generic computer implementation of the abstract idea identified in Prong One. None of the additional elements recited "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Alice Corp., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
At the levels of abstraction described above, the claims do not readily lend themselves to a finding that they are directed to a nonabstract idea. Therefore, the analysis proceeds to step 2B. See BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1349 (Fed. Cir. 2016) ("The Enfish claims, understood in light of their specific limitations, were unambiguously directed to an improvement in computer capabilities. Here, in contrast, the claims and their specific limitations do not readily lend themselves to a step-one finding that they are directed to a nonabstract idea. We therefore defer our consideration of the specific claim limitations’ narrowing effect for step two.") (citations omitted).
MPEP 2106 Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the same reasons as presented in Step 2A Prong 2 (i.e., they amount to nothing more than a general link to a particular technological environment and instructions to apply it there). Moreover, the additional elements recited are known and conventional computing elements (computing system, computer, processors, memory having stored thereon instructions, non-transitory computer-readable medium having stored thereon instructions, training parameters for machine learning, browser-based interface, input device, machine learning module, iteratively training the machine learning module, wherein the training includes adjusting weights of the machine learning module—see published Specification ¶¶ 0086-87, 92-94 describing these at a high level of generality and in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy the statutory disclosure requirements). Specifically with respect to iterative training of the model, this is incident to the very nature of machine learning as supported by Recentive Analytics above and does not set forth an inventive concept.
The Federal Circuit has recognized that "an invocation of already-available computers that are not themselves plausibly asserted to be an advance, for use in carrying out improved mathematical calculations, amounts to a recitation of what is 'well-understood, routine, [and] conventional.'" SAP Am., Inc. v. InvestPic, LLC, 890 F.3d 1016, 1023 (Fed. Cir. 2018) (alteration in original) (citing Mayo v. Prometheus, 566 U.S. 66, 73 (2012)). Apart from the instructions to implement the abstract idea, they only serve to perform well-understood functions (e.g., receiving, storing, retrieving, transmitting data—see Specification above as well as Alice Corp.; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016); and Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) covering the well-known nature of these basic computer functions).
"The use and arrangement of conventional and generic computer components recited in the claims—such as a database, user terminal, and server— do not transform the claim, as a whole, into 'significantly more' than a claim to the abstract idea itself. We have repeatedly held that such invocations of computers and networks that are not even arguably inventive are insufficient to pass the test of an inventive concept in the application of an abstract idea." Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1056 (Fed. Cir. 2017) (citations and quotation marks omitted). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Dependent Claims Step 2A:
The limitations of the dependent claims but for those addressed below merely set forth further refinements of the abstract idea without changing the analysis already presented (i.e., they merely narrow the same abstract idea identified above without adding any new additional elements beyond it). Additionally, for the same reasons as above, the limitations fail to integrate the abstract idea into a practical application because they use the same general technological environment and instructions to implement the abstract idea as the independent claims (i.e., generic computers and generic machine learning).
Claims 2, 9, and 16 recite "creating, retrieving, and storing machine learning models, and wherein the machine learning models include at least one of recurrent neural networks, convolutional neural networks, and deep learning neural networks."
Claims 3, 10, and 17 recite "serializing and deserializing the machine learning models."
Claims 4, 11, and 18 recite "a regression neural network."
Claims 5, 12, and 19 recite a web server.
Claims 6, 13, and 20 recite "to train the machine learning model using a Bayesian model, and wherein the training includes dividing data sets into training, validation, and testing subsets."
Claims 7 and 14 recite "an artificial neural network having an input layer, one or more hidden layers, and an output layer, and wherein each layer includes an arbitrary number of neurons configured to process input parameters and generate a prediction."
All of these are broadly applicable computerized and machine learning elements that are applicable in any environment, do not improve machine learning or any other technology itself, and are used as tools employed for the abstract function of legal document review that was traditionally performed by humans. Even when viewed in combination, they amount to nothing more than generally linking the abstract idea to a particular technological environment.
Dependent Claims Step 2B:
The dependent claims merely use the same general technological environment and instructions to implement the abstract idea. Although they add the elements identified in 2A above, these do not amount to significantly more for the same reasons they fail to integrate the abstract idea into a practical application (i.e., they are broadly applicable computerized and machine learning elements used as tools employed for the abstract function of legal document review).
Moreover, the Specification also indicates this is the routine use of well-known components for the same reasons presented with respect to the elements in the independent claims above (i.e., by describing them at a high level of generality and absent any significant technical detail, thus demonstrating that the inventor considered these elements to be sufficiently well-known that those particulars were not required to fulfill the statutory disclosure requirements: see ¶¶ 0086-87—claims 2-4, 6, 9-11, 13, 16-18, and 20; ¶ 0090—claims 5, 12, and 19; ¶ 0088—claims 7 and 14). Accordingly, they are not directed to significantly more than the exception itself even when viewed in combination, and are not eligible subject matter under § 101.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL VETTER whose telephone number is (571)270-1366. The examiner can normally be reached M-F 9:00-6:00.
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/DANIEL VETTER/Primary Examiner, Art Unit 3628