DETAILED ACTION
This Final Office Action is in response to the arguments and amendments filed December 1, 2025.
Claims 1, 2, 6, 7, 9, 11-13, 17, 18, and 20-29 are currently pending and have been considered below.
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 .
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, 2, 6, 7, 9, 11-13, 17, 18, and 20-29 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards non-eligible subject matter.
In terms of Step 1, claims 1, 2, 6, 7, 9, 11-13, 17, 18, and 20-29 are directed towards one of the four categories of statutory subject matter.
In terms of Step 2(a)(1), independent claims 1, 12, and 20 are directed towards (as represented by claim 1), “detect a trigger event for determining a value of a given project attribute for a given construction project having a stored set of project attribute data within a digital representation of the given construction project that is; in response to detecting the trigger event, execute an attribute-specific set of predictive analytics pipelines for predicting values of the given project attribute, when executed, functions to: obtain one or more electronic drawings for the given construction project; provide the first set of one or more textual elements as input to a first Al model of the first predictive analytics pipeline and thereby cause the first Al model to output a first prediction based on the first set of one or more textual elements; and based on the first prediction that is output by the first Al model of the first predictive analytics pipeline, determine and output a first value of the given project attribute for the given construction project; and wherein a second predictive analytics pipeline in the attribute-specific set of predictive analytics pipelines, when executed, functions to: obtain one or more electronic specifications for the given construction project: and based on the second prediction that is output by the second Al model of the second predictive analytics pipeline, determine and output a second value of the given project attribute for the given construction project and update the stored set of project attribute data for the given construction project within the digital representation of the given construction project that is maintained by the construction management software application based on the first and second values of the given project attribute that are predicted for the given construction project”. The claims are describing receiving information, analyzing with an AI model, and outputting the results (in terms of updating the project with the digital representation. This further includes the detecting a trigger that is described in the originally filed specification as provided/requested information by a user [323-326]. The analysis performed is at a high level using merely AI model in terms of providing the value/output of the collected information. As such, the claims are describing a collection, high level analysis, and display of the results that falls into the abstract idea grouping of mental process.
Additionally, the claims are describing an artificial intelligence system that provides pre-processed information that is then provided as an input to an AI model to output project attribute information. The claims are describing a mathematical calculation in terms of utilizing artificial intelligence to calculate an output for project management. As such, the claims are directed towards an abstract idea under the mathematical concepts grouping.
Step 2(a)(II) considers the additional elements in terms of being transformative into a practical application. The additional elements of the independent claims are, “A computing platform comprising: at least one communication interface; at least one processor; at least one non-transitory computer-readable medium; and program instructions for a construction management software application that are stored on the at least one non-transitory computer-readable medium, wherein the program instructions, when executed by the at least one processor, cause the computing platform to (claim 1); A non-transitory computer-readable medium, wherein the non-transitory computer-readable medium is provisioned with program instructions for a construction management software application that, when executed by at least one processor, cause a computing platform to (claim 12); A method carried out by a back-end computing platform for a construction management software application, the method comprising (claim 20); maintained by the construction management software application; wherein each respective predictive analytics pipeline in the attribute-specific set of predictive analytics pipelines comprises (i) respective pre- processing logic and (ii) a respective artificial intelligence (AI) model, wherein a first predictive analytics pipeline in the attribute-specific set of predictive analytics pipelines, apply first pre-processing logic of the first predictive analytics pipeline to the one or more electronic drawings for the given construction project and thereby identify a first set of one or more textual elements within the one or more electronic drawings; apply second pre-processing logic of the second predictive analytics pipeline to the one or more electronic specifications for the given construction project and thereby identify a second set of one or more textual elements within the one or more electronic specifications provide the second set of one or more textual elements as input to a second Al model of the second predictive analytics pipeline and thereby cause the second Al model to output a second prediction based on the second set of one or more textual elements, wherein the second Al model differs from the first Al model”. The additional elements of the computer elements are described in the originally filed specification [36-42] and figures 1, 6, and 7. The computer elements are described in terms of generic technology to implement the abstract idea. The computer elements are merely tools and are not describing a technical improvement. Examiner notes that while the pre-processing, updating, and AI models are describing the abstract idea, in terms of compact prosecution they will further be considered as additional elements. The AI, updating, and pre-processing are described in the originally filed specification [43-46, 58-66, 110-114, and 324-327] and figures 2, 3A, and 3B. The additional elements with respect to the pre-processing, updating, and AI models are merely describing generic technology to implement the abstract idea. Examiner notes that the AI is further described as ML/AI models developed by others that are utilized which falls within the consideration that these are tools to implement the abstract idea. The pre-processing and updating are merely describing aspects of the AI modeling that further describes the techniques which are generic techniques to implement the AI modeling system. The pre-processing, updating, and AI models are not describing a technical improvement to the AI itself, but rather are merely implementing the abstract idea. As such, the additional elements are not transformative into a practical application. Refer to MPEP 2106.05(f).
Step 2(b) considers the additional elements in terms of being significantly more than the identified abstract idea. The additional elements of the independent claims are, “A computing platform comprising: at least one communication interface; at least one processor; at least one non-transitory computer-readable medium; and program instructions for a construction management software application that are stored on the at least one non-transitory computer-readable medium, wherein the program instructions, when executed by the at least one processor, cause the computing platform to (claim 1); A non-transitory computer-readable medium, wherein the non-transitory computer-readable medium is provisioned with program instructions for a construction management software application that, when executed by at least one processor, cause a computing platform to (claim 12); A method carried out by a back-end computing platform for a construction management software application, the method comprising (claim 20); maintained by the construction management software application; wherein each respective predictive analytics pipeline in the attribute-specific set of predictive analytics pipelines comprises (i) respective pre- processing logic and (ii) a respective artificial intelligence (AI) model, wherein a first predictive analytics pipeline in the attribute-specific set of predictive analytics pipelines, apply first pre-processing logic of the first predictive analytics pipeline to the one or more electronic drawings for the given construction project and thereby identify a first set of one or more textual elements within the one or more electronic drawings; apply second pre-processing logic of the second predictive analytics pipeline to the one or more electronic specifications for the given construction project and thereby identify a second set of one or more textual elements within the one or more electronic specifications provide the second set of one or more textual elements as input to a second Al model of the second predictive analytics pipeline and thereby cause the second Al model to output a second prediction based on the second set of one or more textual elements, wherein the second Al model differs from the first Al model”. The additional elements of the computer elements are described in the originally filed specification [36-42] and figures 1, 6, and 7. The computer elements are described in terms of generic technology to implement the abstract idea. The computer elements are merely tools and are not describing a technical improvement. Examiner notes that while the pre-processing, updating, and AI models are describing the abstract idea, in terms of compact prosecution they will further be considered as additional elements. The AI, updating, and pre-processing are described in the originally filed specification [43-46, 58-66, 110-114, and 324-327] and figures 2, 3A, and 3B. The additional elements with respect to the pre-processing, updating, and AI models are merely describing generic technology to implement the abstract idea. Examiner notes that the AI is further described as ML/AI models developed by others that are utilized which falls within the consideration that these are tools to implement the abstract idea. The pre-processing and updating are merely describing aspects of the AI modeling that further describes the techniques which are generic techniques to implement the AI modeling system. The pre-processing, updating, and AI models are not describing a technical improvement to the AI itself, but rather are merely implementing the abstract idea. As such, the additional elements are not significantly more than the identified abstract idea. Refer to MPEP 2106.05(f).
Dependent claims 6, 7, 9, 11, 17, 18, and 21-29 are further describing the abstract idea and further describing additional elements beyond those identified above. The claims are directed towards, “wherein the given project attribute comprises one of a project title or a project address”, “wherein thefirst Al model comprises a Bidirectional Encoder Representations from Transformers (BERT) model and the second Al model comprises a Generative Pre-trained Transformer (GPT) model”, “wherein at least one of the first or second Al models comprises a pre-trained model that has been fine-tuned for predicting a value of the given project attribute based on training data”, “wherein at least one of the first or second Al models is remotely hosted by a separate computing platform”, “wherein the first predictive analytics pipelinefurther comprises post-processing logic that is applied to the first prediction output by the first Al model of the first predictive analytics pipeline so as to transform the first prediction into the first value of the given project attribute for the given construction project”, “wherein the first prediction of the first predictive analytics pipeline comprises a predicted set of candidate values of the given project attribute along with corresponding confidence scores, and wherein the post-processing logic of the first predictive analytics pipeline functions to identify and output whichever candidate value of the predicted set of candidate values has a highest corresponding confidence score”, “wherein the first pre-processing logic of the first predictive analytics pipeline comprises one or both of (i) an optical character recognition (OCR) engine or (ii) a pre-trained Bidirectional Encoder Representations from Transformers (BERT) name entity recognition (NER) model”, “wherein the first pre-processing logic of the first predictive analytics pipeline further comprises logic for extracting respective contextual data for each of the first set of one or more textual elements, wherein the respective contextual data for each of the first set of one or more textual elements comprises one or more of spatial data, linguistic data, or relational data, and wherein the respective contextual data for each of the first set of one or more textual elements is provided as input to the first AI model along with the first set of one or more textual elements”, “wherein the second pre-processing logic of the second predictive analytics pipeline comprises logic for (i) identifying a general division within each of the one or more electronic specifications and (ii) extracting the second set of one or more textual elements from the identified general division within each of the one or more electronic specifications”, “wherein the second pre-processing logic of the second predictive analytics pipeline further comprises logic for generating a prompt for the second AI model”, “wherein the first predictive analytics pipeline further comprises post-processing logic that is applied to the first prediction output by the first AI model of the first predictive analytics pipeline so as to transform the first prediction into the first value of the given project attribute for the given construction project”, “wherein: the first pre-processing logic of the first predictive analytics pipeline comprises one or both of (i) an optical character recognition (OCR) engine or (ii) a pre-trained Bidirectional Encoder Representations from Transformers (BERT) name entity recognition (NER) model, and the second pre-processing logic of the second predictive analytics pipeline comprises logic for (i) identifying a general division within each of the one or more electronic specifications and (ii) extracting the second set of one or more textual elements from the identified general division within each of the one or more electronic specifications”, “wherein: the first pre-processing logic of the first predictive analytics pipeline further comprises logic for extracting respective contextual data for each of the first set of one or more textual elements, wherein the respective contextual data for each of the first set of one or more textual elements comprises one or more of spatial data, linguistic data, or relational data, and wherein the respective contextual data for each of the first set of one or more textual elements is provided as input to the first AI model along with the first set of one or more textual elements, and the second pre-processing logic of the second predictive analytics pipeline further comprises logic for generating a prompt for the second AI model”. The claims are further describing the mathematical calculation abstract idea in terms of providing more specific techniques of the artificial intelligence model. This also includes the identified high level analysis for the mental process by providing AI techniques that are not directed towards a technical improvement. This is included in the consideration for the specific generative AI model (BERT/GPT), describing the techniques of discriminative AI models (decision tree/computer-vision), providing that the model includes multiple models and other elements of the predictive pipeline, and further describing the post-processing for the applied output of the model. These elements further describe the AI calculation/analysis elements for the predictive modeling for the construction management information. In terms of additional elements, the AI techniques, pre-processing, and post-processing are described in the originally filed specification [43-46, 58-66, 110-114, and 324-327] and figures 2, 3A, and 3B. The additional elements with respect to the pre-processing, post-processing, and AI models are merely describing generic technology to implement the abstract idea. Examiner notes that the AI is further described as ML/AI models developed by others that are utilized which falls within the consideration that these are tools to implement the abstract idea. The pre-processing and post-processing are merely describing aspects of the AI modeling that further describes the techniques which are generic techniques to implement the AI modeling system. The pre-processing, post-processing, and AI models are not describing a technical improvement to the AI itself, but rather are merely implementing the abstract idea. Further, additional elements provide aspects of structural elements in terms of remote elements. The remote elements are described in the originally filed specification [61 and 331]. The specification merely describes that the remote access is an API which is generic technology to implement the abstract idea. Therefore, the claims are not directed towards additional elements that are significantly more or transformative into a practical application. Refer to MPEP 2106.05(f).
The claimed invention is describing an abstract idea without additional elements that are significantly more or transformative into a practical application. Therefore, claims 1, 2, 6, 7, 9, 11-13, 17, 18, and 20-29 are rejected under 35 USC 101 for being directed towards non-eligible subject matter.
Response to Arguments
In response to the arguments filed December 1, 2025 on pages 18-19 regarding the prior art rejection, specifically that the prior art does not teach the amended claim limitations. Examiner agrees. The claim limitations describe a combination of elements for a first and second AI model that is pre-processed and outputs a predictive analysis for a digital representation based on drawings and specification aspects. The combination of elements are nonobvious with respect to the considered prior art. While the previous combination provides elements of AI pre-processing in construction management, the prior art does not specifically provide the combination as amended and claimed. Therefore, the 35 USC 103 rejection has been withdrawn, as considered above in light of the amended claim limitations.
In response to the arguments filed December 1, 2025 on pages 12-18 regarding the 35 USC 101 rejection, specifically that the amended claim limitations are directed towards eligible subject matter.
Examiner respectfully disagrees.
The arguments discuss and allege that the claimed invention is providing a technical improvement with respect to predictive analytics for construction management analysis. The arguments describe aspects in terms of the pre-processing and analysis using the AI models. In response, the models and pre-processing were considered above both in light of the abstract idea and as additional elements. The AI models, as considered with respect to the originally filed specification, describes generic technology to implement the abstract idea and further describes the identified abstract idea. The specification provides named techniques, however, based on the specification the models are pre-trained and “off-the-shelf” modeling systems that are used as tools to implement the identified abstract idea. The use of a first and second model is merely using multiple tools to implement the identified abstract idea. The claims are not directed towards claim limitations that are significantly more or transformative into a practical application. Refer to MPEP 2106.05(f). Therefore, the claimed invention is maintaining the 35 USC 101 rejection, as considered above.
Lacking any further arguments, claims 1, 2, 6, 7, 9, 11-13, 17, 18, and 20-29 are maintaining the 35 USC 101 rejection, as considered above in light of the amended and newly added claim limitations.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Nandakumar [2022/0138004] (AI pipeline analytics);
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 ANDREW CHASE LAKHANI whose telephone number is (571)272-5687. The examiner can normally be reached M-F 730am - 5pm (EST).
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/ANDREW CHASE LAKHANI/Primary Examiner, Art Unit 3629