DETAILED ACTION
This Action is in response to the RCE Amendment for Application Number 19444017 received on 6/25/2026.
Claims 1-30 are presented for examination.
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 .
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 6/18/2026 has been entered.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-14, 21-28, and 30 are rejected under 35 U.S.C. 103 as being unpatentable over Durairaj et al. (US 20240039873) in view of Ferris et al. (US 20240283868) and further in view of Bisztrai et al. (US 20210075832).
Regarding claim 1, Durairaj disclosed a system for providing a simulated browsing session, the system comprising:
a user device (Durairaj, [0066], “a user (e.g., customer) may encounter difficulties in navigating or troubleshooting a webpage or other web-based or software-based solution on a user device 102, which may require a form or other user-enterable content to be supplied by the user, in which case the user may reach out to a contact center system for guidance via an interaction interface 104.”; [0070], “the user has authorized a co-browsing session for assistance (e.g., completing a web-based form);
a cloud browser (Durairaj, [0062], “chat bot may proactively offer the user an opportunity to participate in a co-browse session, and upon user consent, the chat bot may automatically perform a set of desired actions (e.g., web actions) on a webpage with which the user is interacting through embedded JavaScript and/or other technologies.” That is, Durairaj’s chatbot performs actions on a webpage in correspondence with the user’s device and the chatbot is located in the cloud based system such as cloud based system 300 of Fig. 3. Therefore, Durairaj’s chatbot reasonably amounts to the claimed cloud browser, as defined in claim 2. See also [0075], Durairaj provides embodiments where the cobrowse script may “form a portion of, constitute a feature/device superset of, or otherwise involve a cloud-based system similar to the cloud-based system 300 of FIG. 3”; See also [0081]; The chatbot functions to implement a co-browse session and performs actions on the webpage and therefore reasonably amounts to the claimed cloud browser; See also [0070] in which Durairaj disclosed the various actions to be executed by the chatbot such as “ mouse movements/interactions, screen pointers, screen changes, audio/video instructions, text entry, and/or other actions”);
an application programming interface (API) (Durairaj, [0065], “intent classification application programming interface (API) 106”; [0119], “media augmentation system 316 may be embodied as any service or system capable of specifying how the portions of the cloud-based system 300… interact with each other and otherwise performing the functions described herein. In some embodiments, the media augmentation system 316 may be embodied as or include an application program interface (API)”); and
a processor (Durairaj, [0123], “one or more processors executing computer program instructions and interacting with other system components for performing the various functionalities described herein”) configured to:
receive, from the user device, data identifying an online action (Durairaj, [0066], “a user (e.g., customer) may encounter difficulties in navigating or troubleshooting a webpage or other web-based or software-based solution on a user device 102, which may require a form or other user-enterable content to be supplied by the user, in which case the user may reach out to a contact center system for guidance via an interaction interface 104.”; [0070], “the user has authorized a co-browsing session for assistance (e.g., completing a web-based form).” and “the user herself may proactively request assistance for a co-browse session with the bot and engage in the co-browse session”; Proactively requesting assistance for a co-browse session involves providing task data identifying the online task of the particular co-browse session the user needs assistance with);
select, based on the online action, one or both of the cloud browser or the API for executing the online action (Durairaj, [0144], Durairaj disclosed determining whether an incomplete co-browse session is stored by accessing a database, and if the user opts to resume an incomplete co-browse session, the system determines that it needs to retrieve an intent configuration file; Upon opting in to resume an incomplete co-browse session, the system determines to retrieve the intent configuration file from the intent configuration data store 110. This access would utilize the media augmentation system 316 which amounts to an API, in order to access the information from the database/data structure. Therefore, upon a determination of an imcomplete cobrowse session and the user opting in, the system selects both the chatbot/cobrowse script and API for executing the online action) wherein when the cloud browser is selected, the cloud browser is configured to fetch and render online content and interact with the online content (Durairaj, [0062], “chat bot may proactively offer the user an opportunity to participate in a co-browse session, and upon user consent, the chat bot may automatically perform a set of desired actions (e.g., web actions) on a webpage with which the user is interacting through embedded JavaScript and/or other technologies.”; The chatbot performing a set of desired actions on a webpage requires the chatbot fetching and rendering the web content of the web page in order to perform such desired actions);
execute the online action, using the one or both of the cloud browser or the API selected for executing the online action, to generate a result (Durairaj, [0144], and [0119], As explained in preceding mapping, utilization of one or both to handle the relevant co-browse session and retrieving the configuration file);
communicate, to the user device, the result of executing the online action (Durairaj, [0062], “the chat bot may automatically perform a set of desired actions (e.g., web actions) on a webpage with which the user is interacting”; [0138], Durairaj disclosed the chatbot/cobrowse script performing the actions such as mouse movements/interactions, screen pointers, screen changes, audio/video instructions, text entry, and or other actions; [0140], “the chat bot then performs the relevant co-browse actions through the embedded JavaScript within the relevant webpage(s)”; See Fig. 10-11, involving plural communications between chatbot and user device, involving multiple results being communicated); and
in response to communicating the result to the user device, receive, from the user device, another data identifying another online action that is determined by the user device based on at least one of the result of executing the online action or a task previously defined by at least one of the user device or a human user interacting with the AI controlled agent (Durairaj, Fig. 10-11, Durairaj disclosed involving plural communications between chatbot and user device, each requiring additional actions be identified and performed by the chatbot/co-browse script throughout the communications based on the human device inputs).
While Durairaj disclosed communication between the system and a user device, Durairaj did not explicitly disclose the system in communication with an artificial intelligence (AI) controlled agent, in which the another action is determined autonomously by the AI controlled agent.
Ferris disclosed simulated interactions for training contact center agents with respect to assisting customers over a co-browsing communication, in which the another action is determined autonomously by the AI controlled agent. (Ferris, [0029]) Ferris disclosed a customer bot to facilitate training of agents in a contact center conducting a simulated interaction of the interaction type by transmitting one or more customer-statements generated by the customer bot to the first agent and receiving one or more statements made by the first agent in response (Ferris, [0003]), in which the contact center system 200 may be used to engage and manage interactions in which automated processes (or bots) or human agents communicate with customers (Ferris, [0029]) by exchanging messages between parties that may be automated processes, such as bots or chatbots (Ferris, [0057]). Ferris disclosed “the use of customer-side chatbots configured to interact with agents and chatbots of contact centers on a customer's behalf”; [0060] Ferris disclosed scenarios as simulated by customer bots can be directly based on what is presently being detected in the interaction environment of the contact center (Ferris, [0169]).
One of ordinary skill in the art would have been motivated to combine the teachings of Durairaj and Ferris, as they both involve the training of chatbot agents at a contact center (Durairaj, [0074], [0100], Ferris, [0051], [0083]), and as such, they are within similar environments. Furthermore, as Durairaj explicitly suggests that the prediction/behavior models “also may be implemented on customer systems (or, as also used herein, on the “customer-side” of the interaction) and used for the benefit of customers” (Durairaj, [0100]), such would have led one of ordinary skill to incorporate such the customer-side teachings of Ferris within the teachings of Durairaj.
Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to utilize the customer bot of Ferris in place of the human user device of Durairaj in order to provide additional measures for training the contact center via simulated interactions and automation for training agents which favorably remove the need for time-consuming and cumbersome interactions of using training personnel to monitor live calls (Ferris, [0002])), thereby increasing efficiency as a whole.
Durairaj and Ferris did not explicitly disclose the cloud browser generating from the rendered online content, frame data including rendered frames.
In an analogous art, Bisztrai disclosed fetching and rendering online content and generating from the rendered online content, frame data including rendered frames (Bisztrai, [0041]-[0042] and [0047]. Bisztrai disclosed a cloud browser creating and encoding raw/frame data from a fetched/rendered webpage into a stream of frames for real-time streaming to clients to update their screens).
One of ordinary skill in the art would have been motivated to combine the teachings of Durairaj/Ferris and Bisztrai since Durairaj explicitly suggests the utilization of other technologies for interacting with a webpage with which the user is interacting (Durairaj, [0062], “chat bot may proactively offer the user an opportunity to participate in a co-browse session, and upon user consent, the chat bot may automatically perform a set of desired actions (e.g., web actions) on a webpage with which the user is interacting through embedded JavaScript and/or other technologies.”) and Bisztrai explicitly provides such other technologies, and therefore the motivation to combine is found within the references themselves. As Durairaj explicitly suggests the utilization of other technologies for implementing a collaborative browsing environment, such would have led one of ordinary skill in the art at the time the invention was filed to incorporate the utilization of Bisztrai’s cloud browser technology for implementing the shared session of Durairaj.
Therefore it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate Bisztrai’s cloud browser technology within the chatbot cloud browser of Durairaj/Ferris to obtain predictable results of utilizing a well-known cloud browser technology that eliminates dependency on the site/page DOM and facilitates interactions between components, optimizing functionality across devices (Bisztrai, [0003], [0048]).
Claim 23 recites a method with limitations that are substantially similar to the limitations of claim 1. As shown by the above rejection, the combination of Durairaj Ferris and Bisztrai disclosed such limitations. Claim 23 is therefore rejected under the same rationale applied above.
Regarding claims 2 and 24, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the another online action is determined autonomously by the AI controlled agent as a prediction based on the at least one of the result or the task (Durairaj, [0100], Durairaj disclosed “predictors or models based on collected data, such as, for example, customer data, agent data, and interaction data. The models may include behavior models of customers or agents. The behavior models may be used to predict behaviors of, for example, customers or agents, in a variety of situations, thereby allowing embodiments of the technology to tailor interactions based on such predictions… such behavior models also may be implemented on customer systems (or, as also used herein, on the “customer-side” of the interaction) and used for the benefit of customers”; Ferris, [0060], [0169], Ferris disclosed the use of customer-side chatbots configured to interact with agents and chatbots of contact centers on a customer's behalf in which scenarios as simulated by customer bots can be directly based on what is presently being detected in the interaction environment of the contact center; See also [0051], “the analytics module 250 also may generate, update, train, and modify predictors or models 252 based on collected data, such as, for example, customer data, agent data, and interaction data. The models 252 may include behavior models of customers or agents. The behavior models may be used to predict behaviors of, for example, customers or agents, in a variety of situations, thereby allowing embodiments of the present invention to tailor interactions based on such predictions“).
Regarding claims 3 and 25, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the system is a server remotely located from and configured to communicate with the human user device via a network (Durairaj [0062], “chat bot may proactively offer the user an opportunity to participate in a co-browse session, and upon user consent, the chat bot may automatically perform a set of desired actions (e.g., web actions) on a webpage with which the user is interacting through embedded JavaScript and/or other technologies.” That is, Durairaj’s chatbot performs actions on a webpage in correspondence with the user’s device and the chatbot is located in the cloud based system such as cloud based system 300 of Fig. 3. Therefore, Durairaj’s chatbot reasonably amounts to the claimed cloud browser. See also [0075], Durairaj provides embodiments where the cobrowse script may “form a portion of, constitute a feature/device superset of, or otherwise involve a cloud-based system similar to the cloud-based system 300 of FIG. 3”; See also [0081]; The chatbot functions to implement a co-browse session and performs actions on the webpage and therefore reasonably amounts to the claimed cloud browser; See also [0070] in which Durairaj disclosed the various actions to be executed by the chatbot such as “ mouse movements/interactions, screen pointers, screen changes, audio/video instructions, text entry, and/or other actions”), wherein the API is selected when the online action comprises uploading, at initiation of the simulated browsing session, partially-filled form data to recreate within the cloud browser a state of content previously presented to the human user device prior to the simulated browsing session (The limitation is disclosed by the combined teachings of Durairaj in view of Bisztrai; Durairaj, [0144], “If, in block 612, the user opts to resume the incomplete co-browse session, the method 600 advances to block 614 in which the system 100 retrieves the corresponding intent configuration file from the intent configuration data store 110. Additionally, in block 616, the system 100 determines the action at which the co-browse session was terminated based on data stored in the co-browse action database 112. As indicated above, in some embodiments, the system 100 may monitor and record the actions performed during a co-browse session such that the user can subsequently resume an incomplete co-browse session in the event of a disconnection or disruption during the co-browse session.”; See [0149] “When the customer accepts to continue the co-browse session, the previous incomplete session is restored asynchronously, and the chat bot assists the customer to continue filling out the form on the webpage accessed by the user”; This access would utilize the media augmentation system 316 which amounts to an API, in order to access the information from the database/data structure. Therefore, upon a determination of an incomplete cobrowse session and the user opting in, the system selects both the chatbot/cobrowse script and API for executing the online action; In combination with the above functionality of Bisztrai ad [0046]-[0048], in utilizing Bisztrai’s teachings of generating and providing real-time frames, the combined teachings involve uploading such previous form data to the user device), and wherein the system supports interaction by the human user device with the system using one or more of an online application or an online device (Durairaj, [0062], [0066]).
Regarding claim 4, Durairaj, Ferris, and Bisztrai disclosed the system of claim 3, wherein the one or more of the online application or the online device comprises at least one of a web browser, a computer application, a mobile application, or a web-enabled device (Durairaj, [0062], [0066]).
Regarding claims 5 and 26, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the simulated browsing session is content and device agnostic, and supports interactions with online content (Durairaj, [0066], content is not limited, devices are not limited; [0138], “each intent configuration file may include one or more sequences of the various actions (e.g., mouse movements/interactions, screen pointers, screen changes, audio/video instructions, text entry, and/or other actions) to be executed by the chat bot in order to automatically resolve the user intent”).
Regarding claim 6, Durairaj, Ferris, and Bisztrai disclosed the system of claim 5, wherein the online content includes at least one of standard web content, JavaScript® and/or ECMAScript libraries, mobile applications, desktop applications, virtual worlds, augmented reality experiences, video content, semantic content, rich media content, dropdown menus, input boxes, or div layers (Durairaj, [0066], webpage).
Regarding claims 7 and 27, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the cloud browser comprises at least one of a visual browser or a textual browser, and wherein the processor is further configured to execute the cloud browser to obtain, as the result of executing the online action, at least one of predictive data or perceptual data wherein communicating the result of executing the online action comprises transmitting the at least one of the predictive data or the perceptual data to the AI controlled agent (Durairaj, [0100] Durairaj disclosed, “The models may include behavior models of customers or agents. The behavior models may be used to predict behaviors of, for example, customers or agents, in a variety of situations, thereby allowing embodiments of the technology to tailor interactions based on such predictions”; Figs 10-11 include execution of the actions and obtaining results and transmitting such results; Durairaj additionally disclosed prediction/behavior models “also may be implemented on customer systems (or, as also used herein, on the “customer-side” of the interaction) and used for the benefit of customers); and wherein the another online action is determined by the AI controlled agent based on the at least one of the predictive data or the perceptual data (Durairaj, Figs 10-11 showing the customer side responding to predictive data provided by the chatbot; See also Ferris, [0060], [0169], Ferris disclosed the use of customer-side chatbots configured to interact with agents and chatbots of contact centers on a customer's behalf in which scenarios as simulated by customer bots can be directly based on what is presently being detected in the interaction environment of the contact center; See also [0051], “the analytics module 250 also may generate, update, train, and modify predictors or models 252 based on collected data, such as, for example, customer data, agent data, and interaction data. The models 252 may include behavior models of customers or agents. The behavior models may be used to predict behaviors of, for example, customers or agents, in a variety of situations, thereby allowing embodiments of the present invention to tailor interactions based on such predictions“).
Regarding claim 8, Durairaj, Ferris, and Bisztrai disclosed the system of claim 7, wherein the at least one of the predictive data or the perceptual data includes one or more forms of visual data (Durairaj, [0149], chat bot assists in filling out the form on the webpage).
Regarding claim 9, Durairaj, Ferris, and Bisztrai disclosed the system of claim 7, wherein the at least one of the predictive data or the perceptual data includes one or more of an image, a screenshot, audio, video, text, a frame, or semantic data (Durairaj, Fig. 10-11, Text, [0069] text to speech; [0070], “Each intent configuration file may include one or more sequences of the various actions (e.g., mouse movements/interactions, screen pointers, screen changes, audio/video instructions, text entry, and/or other actions”; See also [0092]).
Regarding claims 10 and 28, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the system further comprises an encoder (Bisztrai, [0047] Bisztrai disclosed the cloud browser creating and encoding raw/frame data into a stream of frames for streaming to the clients), and wherein the processor is further configured to: receive, using the cloud browser, at least one of frame data or raw data as the result of executing the online action (Bisztrai, [0032], “user actions (e.g., clicks, taps, gestures, etc.) and executing them in the cloud browser as if the respective user is present in front of the cloud browser”; [0042], “During the session both participants can navigate the website (e.g., click and scroll)”); and encode, using the encoder, the at least one of the frame data or the raw data to produce an encoded stream of frames (Bisztrai, [0043], “Throughout the co-browse session, the images rendered in the respective local browsers are actually those obtained by the cloud browser and streamed back to the respective endpoints”; [0047] Bisztrai disclosed the cloud browser creating and encoding raw/frame data into a stream of frames for streaming to the clients using particular streaming protocols); wherein communicating the result of executing the online action comprises transmitting the encoded stream of frames to the AI controlled agent (Bisztrai, [0043], “Throughout the co-browse session, the images rendered in the respective local browsers are actually those obtained by the cloud browser and streamed back to the respective endpoints”; [0047] Bisztrai disclosed the cloud browser creating and encoding raw/frame data into a stream of frames for streaming to the clients using particular streaming protocols, and also disclosed real-time streaming to the clients).
One of ordinary skill in the art would have been motivated to combine the teachings of Bisztrai with Durairaj and Ferris as they both provide teachings for co-browsing sessions, and as such they are within similar environments.
Therefore it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the teachings of Bisztrai within Durairaj and Ferris to allow for additional ways for handling a co-browse session and yield the same visual image and behavior regardless of the type of browser being used (Bisztrai, [0003]) thereby increasing desirability of use by its customers.
Regarding claim 11, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the another online action comprises at least one of clicking of a button, simulated clicking of a button, typing of text, simulated typing of text, scrolling through web content, navigating an avatar in a virtual world, navigating to a different web page, starting, pausing, or skipping video content (Durairaj, Fig. 10-11, Text, [0069] text to speech; [0070], “Each intent configuration file may include one or more sequences of the various actions (e.g., mouse movements/interactions, screen pointers, screen changes, audio/video instructions, text entry, and/or other actions”; [0070]).
Regarding claim 12, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the processor is further configured to: select, based on the another online action, one or both of the cloud browser or the API for executing the another online action (Durairaj, [0070], “In some embodiments, the chat bot may require access to personal and/or user-specific information in order to execute the relevant co-browse session, in which case the chat bot may retrieve the relevant data from a corresponding user database and/or data structure.” In such embodiments, this access would also utilize the media augmentation system 316 which amounts to selection of an API, in order to access the information from the database/data structure. See [0119]; As such, based on the needed assistance for the co-browse session, a selection of one or both of the chatbot/co-browse script and API would be made for each action in the sequences of actions from the configuration file);
execute the another online action, using the one or both of the cloud browser or the API selected for executing the another online action (Durairaj, [0138] and [0119], As explained in preceding mapping, utilization of one or both of the chatbot/co-browse script and API would be made for each action in the sequences of actions from the configuration file to be executed; For example if one of the actions in the sequence requires accessing database information, such would require the selection and use of media augmentation system 316 (API) along with the chatbot/cobrowse script for executing the action), to generate a plurality of online sessions that are contemporaneous at least in part; and provide, to the AI controlled agent, a unified contextual state across the plurality of online sessions ([0071], “the system 100 tracks/records the actions performed by the chat bot during a co-browse session in a co-browse action database 112…. the data and/or user identifier may be further associated with the relevant intent, which would account for circumstances in which multiple co-browse sessions for unrelated intents could have been interrupted or otherwise remain incomplete.”; [0073], “Over time, a sufficiently large sample size of agent-led co-browsing sessions (e.g., a predefined threshold) may have been recorded in order for the machine learning system 118 to perform machine learning on the recorded data set to determine the optimal steps to be performed to resolve the relevant intent and create an intent configuration file for the intent to subsequently be automatically executed by the chat bot “).
Regarding claim 13, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the processor is further configured to: support synchronized browsing of online content (Durairaj, [0003], Durairaj disclosed executing a co-browse session between user and agent; Figs. 10-11 disclosed the chatbot supporting synchronous browsing between the chatbot and and user device in which both assist in filling out a web form).
Regarding claim 14, Durairaj, Ferris, and Bisztrai disclosed the system of claim 13, wherein the online content includes at least one of standard web content, JavaScript® and/or ECMAScript libraries, Cascading Style Sheet (CSS) transitions, Scalable Vector Graphics (SVG) animations, Canvas elements, Web Graphics Library (WebGL) elements, or content within iFrames (Durairaj, [0066], webpage).
Regarding claims 21 and 30, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the processor is further configured to: maintain a record of the simulated browsing session, the record identifying the online action and the another online action as having been determined by the AI controlled agent (Durairaj, [0101], interaction database stores all interactions and interaction content (e.g. transcripts of the interactions and events detected therein) Ferris, [0052]).
Regarding claim 22, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, wherein the API is configured to process structured text formats comprising one or more of Hypertext Markup Language (HTML), HTML fragments, Extensible Markup Language (XML), or JavaScript Object Notation (JSON) (Durairaj, [0123], Ferris, [0081]).
Claim(s) 15-16, 18-20, 29 are rejected under 35 U.S.C. 103 as being unpatentable over Durairaj et al. (US 20240039873) in view of Ferris et al. (US 20240283868) and Bisztrai et al. (US 20210075832) and further in view of Matula et al. (US 20220247800).
Regarding claim 15, Durairaj, Ferris, and Bisztrai disclosed the system of claim 1, but did not explicitly disclose wherein the processor is further configured to: enforce one or more safeguards.
In an analogous art, Matula disclosed wherein the processor is further configured to: enforce one or more safeguards (Matula, [0045] and [0049], Matula disclosed server enforcing safeguards with respect to security attributes with respect to redactions, and authorization attributes for recipients).
One of ordinary skill in the art would have been motivated to combine the teachings of Matula with Durairaj, Ferris, and Bisztrai, as they both disclosed functionality with respect to co-browsing sessions, and as such, they are within similar environments.
Therefore it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the selective content sharing functionality of Matula within the teachings of Durairaj, Ferris, and Bisztrai, in order to allow for the user of Durairaj and Ferris, in needing help with their online session, to control the sharing of sensitive information thereby facilitating the user from refraining from exposing sensitive information to an agent, such as the ai agents of Durairaj, for unauthorized use (Matula, [0010]), thereby making the system more desirable to use by its customers.
Regarding claim 16, Durairaj, Ferris, Bisztrai and Matula disclosed the system of claim 15, wherein the one or more safeguards comprise at least one of sensitive element redaction, access controls, human oversight, runtime monitoring, or other operational boundaries relating to AI controlled agent behavior constraints (Matula, [0045] and [0049]).
Regarding claim 18, Durairaj, Ferris, Bisztrai and Matula disclosed the system of claim 15, wherein enforcing the one or more safeguards comprises redacting one or more predetermined safeguarded data fields that are flagged within the underlying code of the online content that is accessed by the cloud browser (Matula, [0050]-[0053], Matula disclosed determining a security attribute for portions includes fields of the content to be shared).
Regarding claim 19, Durairaj, Ferris, Bisztrai and Matula disclosed the system of claim 15, wherein enforcing the one or more safeguards comprises autonomously inferring that at least one of a data field or an action is subject to the one or more safeguards (Matula, [0053], Matula disclosed using machine learning to make a determination on security requirements for redaction).
Regarding claim 20, Durairaj, Ferris, Bisztrai and Matula disclosed the system of claim 15, wherein enforcing the one or more safeguards comprises complying with requirements imposed by one or more regulatory regimes that are applicable to content that is accessed in the simulated browsing session (Matula, [0005-[0007]], Matula disclosed the server implementing the safeaguard while complying with particular security authorizations of agents within the business organization having agents of differing level of authority).
Regarding claim 29, Durairaj, Ferris, and Bisztrai disclosed the method of claim 23, but did not explicitly state further comprising: enforcing, by the processor, one or more safeguards, wherein the one or more safeguards comprise at least one of a whitelist of permissible domains for access, a blacklist of prohibited domains prohibited from access during the simulated browsing session, a requirement imposed by one or more regulatory regimes that are applicable to content that is accessed in the simulated browsing session, sensitive element redaction, access controls, human oversight, runtime monitoring, or other operational boundaries relating to AI controlled agent behavior constraints.
Matula disclosed further comprising: enforcing, by the processor, one or more safeguards, wherein the one or more safeguards comprise at least one of a whitelist of permissible domains for access, a blacklist of prohibited domains prohibited from access during the simulated browsing session, a requirement imposed by one or more regulatory regimes that are applicable to content that is accessed in the simulated browsing session, sensitive element redaction, access controls, human oversight, runtime monitoring, or other operational boundaries relating to AI controlled agent behavior constraints (Matula, [0045] and [0049], Matula disclosed server enforcing safeguards with respect to security attributes with respect to redactions, and authorization attributes for recipients).
One of ordinary skill in the art would have been motivated to combine the teachings of Matula with Durairaj, Ferris, and Bisztrai, as they both disclosed functionality with respect to co-browsing sessions, and as such, they are within similar environments.
Therefore it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the selective content sharing functionality of Matula within the teachings of Durairaj, Ferris, and Bisztrai, in order to allow for the user of Durairaj and Ferris, in needing help with their online session, to control the sharing of sensitive information thereby facilitating the user from refraining from exposing sensitive information to an agent, such as the ai agents of Durairaj, for unauthorized use (Matula, [0010]), thereby making the system more desirable to use by its customers.
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Durairaj et al. (US 20240039873) in view of Ferris et al. (US 20240283868) and Bisztrai et al. (US 20210075832) and further in view of Jones et al. (US 20180219849).
Regarding claim 17, Durairaj, Ferris, and Bisztrai disclosed the system of claim 15, but did not explicitly disclose wherein the one or more safeguards comprise at least one of a whitelist of permissible domains for access or a blacklist of prohibited domains prohibited from access during the simulated browsing session.
Jones disclosed wherein the one or more safeguards comprise at least one of a whitelist of permissible domains for access or a blacklist of prohibited domains prohibited from access during the simulated browsing session (Jones, [0049] co-browse service implemented at one or more servers; [0061], Jones disclosed acceptance of a co-browse session causing a co-browse extension to be downloaded to the visitor’s browser; [0074]-[0075] involving a whitelist of approved domains).
One of ordinary skill in the art would have been motivated to combine the teachings of Jones with Durairaj, Ferris, and Bisztrai as they both provide teachings for co-browsing sessions, and as such they are within similar environments.
Therefore it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the whitelist feature of Jones within Durairaj, Ferris, and Bisztrai to provide additional security measures for the cobrowsing sessions of Durairaj and Ferris increasing desirability of use by its customers.
Response to Arguments
Applicant’s arguments filed on 6/18/2026 with respect to amended claim(s) 1, 3, 23, 25 have been considered but are moot in view of the new ground of rejection, necessitated by the amendment to these claims, including new limitations that change the scope of the invention.
Applicant additionally asserts, “as explained in the previous Amendment and Response to Non-Final Office Action, Ferris fails to disclose, teach, or suggest an AI agent that determines online actions autonomously, as required by independent claims 1 and 23. Examiner respectfully disagrees for the same reasons set forth in the Final Rejection, submitted 5/29/2026. Claim 1 merely recites “receiv[ing], from the AI controlled agent, data identifying an online action”, communicat[ing], to the AI controlled agent, the result of executing the online action” and “in response to communicating the result to the AI controlled agent, receiv[ing] from the AI controlled agent, another data identifying another online action that is determined autonomously by the AI controlled agent based on one at least one of the result of executing the online action or a task previously defined by at least one of the AI controlled agent or a human user interacting with the AI controlled agent. Durairaj in view of Ferris disclosed such limitations. As noted in the rejection, while Durairaj disclosed communication between the system and a user device, Durairaj did not explicitly disclose the system in communication with an artificial intelligence (AI) controlled agent, in which the another action is determined autonomously by the AI controlled agent. Ferris disclosed simulated interactions for training contact center agents with respect to assisting customers over a co-browsing communication, in which the another action is determined autonomously by the AI controlled agent. (Ferris, [0029]) Ferris disclosed a customer bot to facilitate training of agents in a contact center conducting a simulated interaction of the interaction type by transmitting one or more customer-statements generated by the customer bot to the first agent and receiving one or more statements made by the first agent in response (Ferris, [0003]), in which the contact center system 200 may be used to engage and manage interactions in which automated processes (or bots) or human agents communicate with customers (Ferris, [0029]) by exchanging messages between parties that may be automated processes, such as bots or chatbots (Ferris, [0057]). Ferris disclosed “the use of customer-side chatbots configured to interact with agents and chatbots of contact centers on a customer's behalf”; [0060] Ferris disclosed scenarios as simulated by customer bots can be directly based on what is presently being detected in the interaction environment of the contact center (Ferris, [0169]). The claim does not specify any particular techniques of the autonomous determination other than that it is based on certain information and therefore Durairaj in view of Ferris’ automated customer bot reads on the limitation, as explained above.
The rejections are therefore respectfully maintained.
It is the Examiner’s position that Applicant has not yet submitted claims drawn to limitations, which define the operation and apparatus of Applicant’s disclosed invention in manner, which distinguishes over the prior art.
Failure for Applicant to significantly narrow definition/scope of the claims and supply arguments commensurate in scope with the claims implies the Applicant intends broad interpretation be given to the claims. The Examiner has interpreted the claims with scope parallel to the Applicant in the response and reiterates the need for the Applicant to more clearly and distinctly define the claimed invention.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ashkenazi et al. (US 20230297315) disclosed a cloud-based shared browser allowing participants associated with different permission levels with access to the shared browser (Ashkenazi. [0055]).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JERRY B DENNISON whose telephone number is (571)272-3910. The examiner can normally be reached M-F 8:30-5:50.
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/JERRY B DENNISON/Primary Examiner, Art Unit 2409
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