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. Specification Applicant is reminded of the proper content of an abstract of the disclosure. A patent abstract is a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains. The abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art. If the patent is of a basic nature, the entire technical disclosure may be new in the art, and the abstract should be directed to the entire disclosure. If the patent is in the nature of an improvement in an old apparatus, process, product, or composition, the abstract should include the technical disclosure of the improvement. The abstract should also mention by way of example any preferred modifications or alternatives. Where applicable, the abstract should include the following: (1) if a machine or apparatus, its organization and operation; (2) if an article, its method of making; (3) if a chemical compound, its identity and use; (4) if a mixture, its ingredients; (5) if a process, the steps. Extensive mechanical and design details of an apparatus should not be included in the abstract. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length. See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts. Claim Objections Claim 19 is objected to because of the following informalities: “A system for electronic presentation assistance, the system comprising;” should be -- A system for electronic presentation assistance, the system comprising : -- (line 1) . Appropriate correction is required. Claim Rejections - 35 USC § 102 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Viswanathan (U.S. 2020/0043114) . With regard to claim 1, Viswanathan t eaches a method of electronic presentation assistance ([abstract] multimedia training guide/content ) , the method comprising: receiving, via an artificial intelligence assistant computing facility ([0077] to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar ) or a component or a module thereof, one or more presentations made available by a first user, the one or more presentations comprising slides ([0077] to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated ) ; receiving, via the artificial intelligence assistant computing facility or the component or the module thereof, a request from a second user to generate specific content from information extracted from the one or more presentations ([0021] authoring multimedia training content associated with a closed loop marketing content in a second set of user devices operated by a second set of users, storing the created multimedia training content associated with the closed loop marketing content as a network-based resource ; [0037] the second set of user devices operated by the second set of users are configured to author and create multimedia training content through authoring module for any particular closed loop marketing content of closed loop marketing platform and store as network-based resource in an information module ) ; analyzing, via the artificial intelligence assistant computing facility or the component or the module thereof, the one or more presentations to classify data and metadata for the slides ([0022] capturing a second user interactions, with the closed loop marketing content in the background being navigated or changed or marked or opened and/or highlighted certain information in the closed loop marketing content as per video or audio narration timeline and get synchronized as interactivity data or media cue points and combining video with audio, audio, interactivity data and/or media cue points ; [0033] generating an audio from provided narration text data , also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ) ; generating, via the artificial intelligence assistant computing facility or the component or the module thereof, a summary for each of the one or more presentations ([0022] interactivity data or media cue point s and combining video with audio, audio, interactivity data and/or media cue point s as the multimedia training content associated to the closed loop marketing content ; [0076] To summ arise, in the typical embodiment illustrated in FIG. 1A, the authoring module (104) enables second set of user devices (102) operated by second set of users to author multimedia training content (1062) for any particular closed loop marketing content (106) ) ; determining, via the artificial intelligence assistant computing facility or the component or the module thereof, similarities in content ([0074] configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A … This enables the first user to easily refer the multimedia training content (1062) on the foreground and the information written on the background at the same time ) ; determining, via the artificial intelligence assistant computing facility or the component or the module thereof and based on the second user request, a response to the second user request ([0062] the second set of user devices (102) may comprise or may be externally connected to, but not limited to, a closed loop marketing platform (110). The closed loop marketing platform (110) is one or multiple integrated computer software applications run on servers, tablets and mobile used for closed loop marketing with or without Customer Relationship Management (CRM) platform ; [0068] the second set of user devices operated by second set of users access the closed loop marketing platform then within authoring module to author multimedia training content for any particular closed loop marketing content ; [0071] the authoring module (104) captures interactions of a second user of the second set of users with the closed loop marketing content in the background being navigated or changes or marked or opened or highlighted certain information ) ; predicting content edits based at least in part on the second user requests ( [0015] The current invention has integrated authoring tool to create multimedia training content as foreground overlay with video, audio, avatar animation, slide pointer and highlighter animation for any closed loop marketing content and interlink with particular closed loop marketing content slide(s) of closed loop marketing platform ) and reaction to suggestions made via the artificial intelligence assistant computing facility or the component or the module thereof ([0077] by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized. The authoring module (104) may provide an interfaces to create simulation based embedded multimedia training content (1062) comprising a video of a BOT avatar with machine voice as per provided narration script or an audio & video of a second set of users recorded directly in authoring module ) ; generating a compositional change to a slide in a presentation by the second user, via the artificial intelligence assistant computing facility or the component or the module thereof and based at least in part on the second user request, presentation context, and predicted reaction ([0077] by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized ) ; and generating a compositional change to the presentation by the second user, via the artificial intelligence assistant computing facility or the component or the module thereof and based at least in part on the second user request, presentation context, and predicted reaction ( [0071] the authoring module (104) captures interactions of a second user of the second set of users with the closed loop marketing content in the background being navigated or chang es or marked or opened or highlighted certain information in the closed loop marketing content as per video or audio narration timeline and get synchronized as media cue points and/or interactivity data ; [0077] by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized ) . With regard to claim 2 , the limitations are addressed above and Viswanathan teaches further comprising: assessing, via the artificial intelligence assistant computing facility or the component or the module thereof, the meaning of each slide in the one or more presentations ( [0003] Typically, these digital materials are developed as a set of presentation slid es and each slid e may represent a key message or scientific information to be communicated with HCP during the call along with appropriate references ; [0014] The present invention provides field team an instant access to multimedia training content anytime like an help within the closed loop marketing platform along with particular closed loop marketing content (Digital materials) slid e wise explaining “why” and “how” to present a particular key message or a slid e ) ; determining, via the artificial intelligence assistant computing facility or the component or the module thereof, font, color, shapes and/or images from each slide in the one or more presentations ( Figs. 3A-3D; [0074] configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A . Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B. In one embodiment shown in FIG. 3C, the multimedia training content (1062) is draggable and movable as foreground overlay on top of closed loop marketing content (106) ) ; and identifying, via the artificial intelligence assistant computing facility or the component or the module thereof, text and images from slides, charts, and/or graphs (Figs. 3A-3D; [0030] the synthesising includes speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ; [0071] It may include speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ) . With regard to claim 3 , the limitations are addressed above and Viswanathan teaches further comprising: classifying, via the artificial intelligence assistant computing facility or the component or the module thereof, the content from each slide in the one or more presentations ([0022] capturing a second user interactions, with the closed loop marketing content in the background being navigated or changed or marked or opened and/or highlighted certain information in the closed loop marketing content as per video or audio narration timeline and get synchronized as interactivity data or media cue points and combining video with audio, audio, interactivity data and/or media cue points ; [0033] generating an audio from provided narration text data , also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data) ; and determining, via the artificial intelligence assistant computing facility or the component or the module thereof, relevant topical categories and sub-categories for each slide in the one or more presentations ( [0006] Many e-learning, blended learning solutions are developed and used in a print and digital form using Learning management systems to get trained on these top ics discussed in digital materials ; [0016] These multimedia training content load and play as foreground overlay on top of any particular closed loop marketing content being opened in the closed loop marketing platform ) . With regard to claim 4 , the limitations are addressed above and Viswanathan teaches further comprising: summarizing, via an artificial intelligence assistant computing facility, the presentation ([0077] the authoring module (104) may be configured to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated ) ; wherein generating, via the artificial intelligence assistant computing facility or the component or the module thereof, a summary of presentation content for each of the one or more presentations ( [0074] Then, at step 208, the first set of user devices (108) are configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A. Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B ) . With regard to claim 5 , the limitations are addressed above and Viswanathan teaches further comprising: determining, via the artificial intelligence assistant computing facility or the component or the module thereof, similarities between content of the one or more presentations, wherein the similarities between content of the one or more presentations are identified using vector representation of text and the slide metadata (Figs. 3A-3D; [0030] the synthesising includes speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ; [0071] It may include speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ) . With regard to claim 6 , the limitations are addressed above and Viswanathan teaches further comprising: identifying, via the artificial intelligence assistant computing facility or the component or the module thereof, answers to questions posed by the second user ( [0015] The current invention has integrated authoring tool to create multimedia training content as foreground overlay with video, audio, avatar animation, slide pointer and highlighter animation for any closed loop marketing content and interlink with particular closed loop marketing content slide(s) of closed loop marketing platform ; [0077] by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized. The authoring module (104) may provide an interfaces to create simulation based embedded multimedia training content (1062) comprising a video of a BOT avatar with machine voice as per provided narration script or an audio & video of a second set of users recorded directly in authoring module) wherein the artificial intelligence assistant computing facility or the component or the module thereof determines a best answer using a search lookup to generate a set of best possible answers ([0021] authoring multimedia training content associated with a closed loop marketing content in a second set of user devices operated by a second set of users, storing the created multimedia training content associated with the closed loop marketing content as a network-based resource; [0037] the second set of user devices operated by the second set of users are configured to author and create multimedia training content through authoring module for any particular closed loop marketing content of closed loop marketing platform and store as network-based resource in an information module) and then uses deep learning to analyze and extract the best answer from candidate document results generated by the search lookup ([0074] Then, at step 208, the first set of user devices (108) are configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A. Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B) . With regard to claim 7 , the limitations are addressed above and Viswanathan teaches further comprising: predicting, via the artificial intelligence assistant computing facility or the component or the module thereof, a set of slides and a slide sequence for a presentation in response to the second user request wherein the artificial intelligence assistant computing facility or the component or the module thereof ( [0015] The current invention has integrated authoring tool to create multimedia training content as foreground overlay with video, audio, avatar animation, slide pointer and highlighter animation for any closed loop marketing content and interlink with particular closed loop marketing content slide(s) of closed loop marketing platform) , predicts the set of slides and the slide sequence based on topic similarity ([0077] to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated ) , usage frequency ([0074] The same has been illustrated in FIG. 3A. Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B … This enables the first user to easily refer the multimedia training content (1062) on the foreground and the information written on the background at the same time ) , presentation metadata similarity ([0022] capturing a second user interactions, with the closed loop marketing content in the background being navigated or changed or marked or opened and/or highlighted certain information in the closed loop marketing content as per video or audio narration timeline and get synchronized as interactivity data or media cue points and combining video with audio, audio, interactivity data and/or media cue points ; [0033] generating an audio from provided narration text data , also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data) , and desired presentation length ([0075] the first set of user devices (108) are configured to render and play the multimedia training content (1062) … in sync with video or audio narration timeline as per interactivity data or media cue points data ) . With regard to claim 8 , the limitations are addressed above and Viswanathan teaches further comprising: predicting, via the artificial intelligence assistant computing facility or the component or the module thereof, a content edit in a slide using machine learning technology ([0074] the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B. In one embodiment shown in FIG. 3C, the multimedia training content (1062) is draggable and movable as foreground overlay on top of closed loop marketing content ; [0077] by using Artificial Intelligence based BOT avatar, machi ne voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/ machin e voice narration or description and get synchronized ) . With regard to claim 9 , the limitations are addressed above and Viswanathan teaches further comprising: composing, via the artificial intelligence assistant computing facility or the component or the module thereof, a new slide based on a context data of an existing slide ([0077] machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized … uploaded existing media content to render/play as an overlay content on top of the digital material slides within the closed loop marketing platform (110) ) . With regard to claim 10 , the limitations are addressed above and Viswanathan teaches further comprising: generating, via the artificial intelligence assistant computing facility or the component or the module thereof, a new presentation ([0077] machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized … uploaded existing media content to render/play as an overlay content on top of the digital material slides within the closed loop marketing platform (110) ) ; wherein the new presentation where the presentation comprises an initial slide selected by the second user ( [0077] authoring module (104) may provide an interfaces to create simulation based embedded multimedia training content (1062) comprising a video of a BOT avatar with machine voice as per provided narration script or an audio & video of a second set of users recorded directly in authoring module (104) or uploaded existing media content to render/play as an overlay content on top of the digital material slides within the closed loop marketing platform (110) ) and a slide created by the artificial intelligence assistant computing facility or the component or the module thereof with inherited style and layout properties from the initial slide ([0074] the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B. In one embodiment shown in FIG. 3C, the multimedia training content (1062) is draggable and movable as foreground overlay on top of closed loop marketing content (106) ) . With regard to claim 1 1 , Viswanathan teaches a computer readable medium containing software capable of performing the method according to claim 1 ( [0027] In accordance with an embodiment of the present invention, the closed loop marketing platform is one or multiple integrated computer soft ware applications run on servers, tablets and mobile used for closed loop marketing with or without customer relationship management platform ; [0063] the machine-readable instructions may be loaded in a form of a computer soft ware program into the memory unit ) . With regard to claim 1 2 , Viswanathan teaches a system for electronic presentation assistance ([abstract] multimedia training guide/content ) , the system comprising; an artificial intelligence assistant computing facility ([0077] to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar ) including: at least one processor ([0064] the authoring module includes a processor) ; and a memory device storing software ( [0063] may be loaded into the memory unit ) configured to cause the at least one processor to: receive one or more presentations comprising a slide made available by a first user ([0077] to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated ) ; receive a request from a second user to generate specific content from information extracted from the one or more presentations ([0021] authoring multimedia training content associated with a closed loop marketing content in a second set of user devices operated by a second set of users, storing the created multimedia training content associated with the closed loop marketing content as a network-based resource ; [0037] the second set of user devices operated by the second set of users are configured to author and create multimedia training content through authoring module for any particular closed loop marketing content of closed loop marketing platform and store as network-based resource in an information module ) ; analyze the one or more presentations to classify data and metadata for each slide of the one or more presentations ([0022] capturing a second user interactions, with the closed loop marketing content in the background being navigated or changed or marked or opened and/or highlighted certain information in the closed loop marketing content as per video or audio narration timeline and get synchronized as interactivity data or media cue points and combining video with audio, audio, interactivity data and/or media cue points ; [0033] generating an audio from provided narration text data , also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data) ; generate a summary for each of the one or more presentations ([0022] interactivity data or media cue point s and combining video with audio, audio, interactivity data and/or media cue point s as the multimedia training content associated to the closed loop marketing content ; [0076] To summ arise, in the typical embodiment illustrated in FIG. 1A, the authoring module (104) enables second set of user devices (102) operated by second set of users to author multimedia training content (1062) for any particular closed loop marketing content (106) ) ; determine content similarities between the one or more presentations ([0074] configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A … This enables the first user to easily refer the multimedia training content (1062) on the foreground and the information written on the background at the same time ) ; predict a content edit based at least in part on the second user request ( [0015] The current invention has integrated authoring tool to create multimedia training content as foreground overlay with video, audio, avatar animation, slide pointer and highlighter animation for any closed loop marketing content and interlink with particular closed loop marketing content slide(s) of closed loop marketing platform) and a reaction to suggestions by the second user ([0077] by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized. The authoring module (104) may provide an interfaces to create simulation based embedded multimedia training content (1062) comprising a video of a BOT avatar with machine voice as per provided narration script or an audio & video of a second set of users recorded directly in authoring module ) ; generate a compositional change to a slide constructed to respond to the second user request based at least in part on a presentation context and a predicted reaction ([0077] by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized ) ; and generate a compositional change to a presentation constructed to respond to the second user request based at least in part on a presentation context and a predicted reaction ([0071] the authoring module (104) captures interactions of a second user of the second set of users with the closed loop marketing content in the background being navigated or chang es or marked or opened or highlighted certain information in the closed loop marketing content as per video or audio narration timeline and get synchronized as media cue points and/or interactivity data ; [0077] by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized ) . With regard to claim 13 , the limitations are addressed above and Viswanathan teaches w herein the processor assesses the meaning of the content from each slide of the one or more presentations ( [0003] Typically, these digital materials are developed as a set of presentation slid es and each slid e may represent a key message or scientific information to be communicated with HCP during the call along with appropriate references ; [0014] The present invention provides field team an instant access to multimedia training content anytime like an help within the closed loop marketing platform along with particular closed loop marketing content (Digital materials) slid e wise explaining “why” and “how” to present a particular key message or a slid e ) by determining font, color, shapes, images from each slide (Figs. 3A-3D; [0074] configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A . Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B. In one embodiment shown in FIG. 3C, the multimedia training content (1062) is draggable and movable as foreground overlay on top of closed loop marketing content (106) ) as well as text and images from slides, charts, and graphs (Figs. 3A-3D; [0030] the synthesising includes speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ; [0071] It may include speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ) ; and classifies the content from each slide of the one or more presentations by determining relevant topical categories and sub- categories for each slide ( [0006] Many e-learning, blended learning solutions are developed and used in a print and digital form using Learning management systems to get trained on these top ics discussed in digital materials ; [0016] These multimedia training content load and play as foreground overlay on top of any particular closed loop marketing content being opened in the closed loop marketing platform ) . With regard to claim 1 4 , the limitations are addressed above and Viswanathan teaches wherein the memory device is further configured to generate a summary of content for each of the one or more presentations ( [0074] Then, at step 208, the first set of user devices (108) are configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A. Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B ) . With regard to claim 1 5 , the limitations are addressed above and Viswanathan teaches wherein the processor is further adapted to determine similar content by identifying the similarity of each slide in the one or more presentations using vector representation of text and slide metadata (Figs. 3A-3D; [0030] the synthesising includes speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ; [0071] It may include speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ) and to identify the similarity of each presentation using vector representation of text, presentation summary, and presentation metadata (Figs. 3A-3D; [0030] the synthesising includes speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ; [0071] It may include speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ) . With regard to claim 1 6 , the limitations are addressed above and Viswanathan teaches wherein the processor predicts content edits in a slide ([0077] to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated ) , a slide for inclusion ([0077] machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized … uploaded existing media content to render/play as an overlay content on top of the digital material slides within the closed loop marketing platform (110) ) , and a slide sequence in a presentation ([0077] machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized … uploaded existing media content to render/play as an overlay content on top of the digital material slides within the closed loop marketing platform (110) ) . With regard to claim 1 7 , the limitations are addressed above and Viswanathan teaches wherein the at least one processor ([0064] the authoring module includes a processor) and a memory device ([0063] may be loaded into the memory unit ) storing an artificial intelligence assistant computing facility ([0077] to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar ) are configured to compose new slides through application of machine learning and generative AI technology based on context provided by slides already added to a presentation by the second user ([0077] authoring module (104) may provide an interfaces to create simulation based embedded multimedia training content (1062) comprising a video of a BOT avatar with machine voice as per provided narration script or an audio & video of a second set of users recorded directly in authoring module (104) or uploaded existing media content to render/play as an overlay content on top of the digital material slides within the closed loop marketing platform (110) ) . With regard to claim 1 8 , the limitations are addressed above and Viswanathan teaches wherein the processor is further configured to generate a new presentation comprising a slide created using generative AI technology ([0077] machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized … uploaded existing media content to render/play as an overlay content on top of the digital material slides within the closed loop marketing platform (110) ) with inherited style and layout properties from an initial slide selected by the second user ([0074] the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B. In one embodiment shown in FIG. 3C, the multimedia training content (1062) is draggable and movable as foreground overlay on top of closed loop marketing content (106) ) . With regard to claim 1 9 , Viswanathan teaches a system for electronic presentation assistance ([abstract] multimedia training guide/content ) , the system comprising : an artificial intelligence assistant computing facility ([0077] to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar ) including: at least one processor ([0064] the authoring module includes a processor) ; and a memory device configured to adapt the at least one processor ([0063] may be loaded into the memory unit ) to: receive one or more presentations made available by a first user ([0077] to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated ) ; receive a request from a second user to answer a specific question from information extracted from the one or more presentations ([0021] authoring multimedia training content associated with a closed loop marketing content in a second set of user devices operated by a second set of users, storing the created multimedia training content associated with the closed loop marketing content as a network-based resource ; [0037] the second set of user devices operated by the second set of users are configured to author and create multimedia training content through authoring module for any particular closed loop marketing content of closed loop marketing platform and store as network-based resource in an information module ) ; analyze the one or more presentations to classify data and metadata for each slide of the one or more presentations ([0022] capturing a second user interactions, with the closed loop marketing content in the background being navigated or changed or marked or opened and/or highlighted certain information in the closed loop marketing content as per video or audio narration timeline and get synchronized as interactivity data or media cue points and combining video with audio, audio, interactivity data and/or media cue points ; [0033] generating an audio from provided narration text data , also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data) ; generate a summary for each of the one or more presentations ([0022] interactivity data or media cue point s and combining video with audio, audio, interactivity data and/or media cue point s as the multimedia training content associated to the closed loop marketing content ; [0076] To summ arise, in the typical embodiment illustrated in FIG. 1A, the authoring module (104) enables second set of user devices (102) operated by second set of users to author multimedia training content (1062) for any particular closed loop marketing content (106) ) ; and generate from information extracted from the one or more presentations a human-readable answer to the specific question posed by the second user ( [0015] The current invention has integrated authoring tool to create multimedia training content as foreground overlay with video, audio, avatar animation, slide pointer and highlighter animation for any closed loop marketing content and interlink with particular closed loop marketing content slide(s) of closed loop marketing platform ; [0077] by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized. The authoring module (104) may provide an interfaces to create simulation based embedded multimedia training content (1062) comprising a video of a BOT avatar with machine voice as per provided narration script or an audio & video of a second set of users recorded directly in authoring module) . With regard to claim 20 , the limitations are addressed above and Viswanathan teaches wherein the human-readable answer to the question posed by the second user are generated by assessing the meaning of each slide ( [0015] The current invention has integrated authoring tool to create multimedia training content as foreground overlay with video, audio, avatar animation, slide pointer and highlighter animation for any closed loop marketing content and interlink with particular closed loop marketing content slide(s) of closed loop marketing platform ; [0077] by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated or changes or marked or highlighted certain information in the slide as per BOT avatar video/audio/machine voice narration or description and get synchronized. The authoring module (104) may provide an interfaces to create simulation based embedded multimedia training content (1062) comprising a video of a BOT avatar with machine voice as per provided narration script or an audio & video of a second set of users recorded directly in authoring module) , classifying the content from each slide ([0022] capturing a second user interactions, with the closed loop marketing content in the background being navigated or changed or marked or opened and/or highlighted certain information in the closed loop marketing content as per video or audio narration timeline and get synchronized as interactivity data or media cue points and combining video with audio, audio, interactivity data and/or media cue points ; [0033] generating an audio from provided narration text data , also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data) , summarizing the presentation ([0077] the authoring module (104) may be configured to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated ) , and generating a best possible answer ( [0074] Then, at step 208, the first set of user devices (108) are configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A. Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B ) ; to assess the meaning of each slide, the at least one processor and a memory device storing an artificial intelligence assistant computing facility is configured to determine font, color, shapes, images from each slide (Figs. 3A-3D; [0074] configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A . Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B. In one embodiment shown in FIG. 3C, the multimedia training content (1062) is draggable and movable as foreground overlay on top of closed loop marketing content (106) ) as well as text and images from slides, charts, and graphs (Figs. 3A-3D; [0030] the synthesising includes speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ; [0071] It may include speech synthesis, generating an audio from provided narration text data, also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data ) ; to classify the content from each slide ([0022] capturing a second user interactions, with the closed loop marketing content in the background being navigated or changed or marked or opened and/or highlighted certain information in the closed loop marketing content as per video or audio narration timeline and get synchronized as interactivity data or media cue points and combining video with audio, audio, interactivity data and/or media cue points ; [0033] generating an audio from provided narration text data , also producing a video of an animated avatar with mouth and lip movements synchronized as per audio narration data) , the at least one processor and a memory device storing an artificial intelligence assistant computing facility is configured to determine relevant topical categories and sub-categories for each slide ( [0006] Many e-learning, blended learning solutions are developed and used in a print and digital form using Learning management systems to get trained on these top ics discussed in digital materials ; [0016] These multimedia training content load and play as foreground overlay on top of any particular closed loop marketing content being opened in the closed loop marketing platform ) ; to summarize the presentation, the at least one processor and a memory device storing an artificial intelligence assistant computing facility is configured to generate a summary of the presentation content ( [0074] Then, at step 208, the first set of user devices (108) are configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A. Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B ; [0077] the authoring module (104) may be configured to create the simulation based embedded multimedia training content (1062), in multiple languages, by using Artificial Intelligence based BOT avatar, machine voice as per provided narration script along with digital material slides being navigated ) ; and to generate the human-readable answer, the at least one processor is configured to use a search lookup to identify a set of possible answers ([0021] authoring multimedia training content associated with a closed loop marketing content in a second set of user devices operated by a second set of users, storing the created multimedia training content associated with the closed loop marketing content as a network-based resource ; [0037] the second set of user devices operated by the second set of users are configured to author and create multimedia training content through authoring module for any particular closed loop marketing content of closed loop marketing platform and store as network-based resource in an information module ) , use deep learning to analyze and extract a best possible answer from the set of possible answers ( [0074] Then, at step 208, the first set of user devices (108) are configured to access a user interface (302) to load associated multimedia training content (1062). The same has been illustrated in FIG. 3A. Further, at step 210, the multimedia training content (1062) is loaded as foreground overlay on top of closed loop marketing content in the background, which has been illustrated in FIG. 3B ) , and use generative AI technology to compose the human-readable answer to the question posed by the second user ( [0015] The current invention has integrated authoring tool to create multimedia training content as foreground overlay with video