Description:TECHNICAL FIELD
[0001] The embodiments of the present disclosure generally relate to interactive purchasing guiding systems. More particularly, the present disclosure relates to a system and a method for interactive purchasing of one or more products.

BACKGROUND
[0002] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admission of the prior art.
[0003] As consumers navigate through numerous conventional platforms for online purchase, they are frequently faced with an abundance of options that may often be daunting to navigate. Traditional search and filtering mechanisms, while helpful, often rely on rigid parameters that may not fully encapsulate the nuanced preferences and individualized needs of consumers. This may result in a frustrating and time-consuming experience for the consumers desiring to make well-informed purchasing decisions.
[0004] There is, therefore, a need in the art to provide a system and a method that can mitigate the problems associated with the conventional platforms and provide a personalized approach for online purchasing.

OBJECTS OF THE PRESENT DISCLOSURE
[0005] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are listed herein below.
[0006] It is an object of the present disclosure to provide a system and a method for interactive purchasing that provides product recommendations to consumers based on inputs provided by the consumers.
[0007] It is an object of the present disclosure to provide a system that generates text-based recommendations associated with the product recommendations using artificial intelligence (AI) techniques.
[0008] It is an object of the present disclosure to provide a system that uses AI techniques to visually represent the text-based recommendations in a form of video presentations.
[0009] It is an object of the present disclosure to provide a system that dynamically updates the video presentations using AI techniques based on inputs provided by consumers and determines a progression of the video presentations in real-time.

SUMMARY
[0010] This section is provided to introduce certain objects and aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
[0011] In an aspect, the present disclosure relates to a system for interactive purchasing. The system includes a processor and a memory operatively coupled with the processor. The memory stores instructions which, when executed, cause the processor to receive information from one or more users. The information is associated with a purchasing category selected by the one or more users. The processor generates via an artificial intelligence (AI) engine, one or more product recommendations based on the information. The processor visually represents the one or more product recommendations. The processor dynamically updates one or more visually represented product recommendations based on one or more inputs provided by the one or more users.
[0012] In an embodiment, the processor may generate the one or more product recommendations by being configured to dynamically filter the information based on the purchasing category selected by the one or more users.
[0013] In an embodiment, the information may include at least one of a product type, a budget range, and a brand preference associated with the purchasing category.
[0014] In an embodiment, the processor may generate one or more text-based recommendations associated with the one or more product recommendations.
[0015] In an embodiment, the processor may visually represent the one or more text-based recommendations into one or more video presentations using the AI engine.
[0016] In an embodiment, the one or more video presentations may include at least one clickable element that enables the one or more users to provide inputs.
[0017] In an embodiment, the processor may dynamically update the one or more visually represented product recommendations based on the one or more inputs provided by the one or more users in real-time and determine progression of the one or more video presentations.
[0018] In an aspect, the present disclosure relates to a method for interactive purchasing. The method includes receiving, by a processor, associated with a system, information from one or more users. The information is associated with a purchasing category selected by the one or more users. The method includes generating, by the processor, via an AI engine, one or more product recommendations based on the information. The method includes visually representing, by the processor, the one or more product recommendations. The method includes dynamically updating, by the processor, the one or more visually represented product recommendations based on one or more inputs provided by the one or more users.
[0019] In an embodiment, the method may include generating, by the processor, the one or more product recommendations by being configured to dynamically filter the information based on the purchasing category selected by the one or more users.
[0020] In an embodiment, the method may include generating, by the processor, one or more text-based recommendations associated with the one or more product recommendations.
[0021] In an embodiment, the method may include visually representing, by the processor, the one or more text-based recommendations into one or more video presentations using the AI engine.
[0022] In an embodiment, the one or more video presentations may include at least one clickable element that enables the one or more users interact and provide the one or more inputs to the system.
[0023] In an embodiment, the method may include dynamically updating, by the processor, the visually represented one or more product recommendations based on the one or more inputs provided by the one or more users in real-time and determining the progression of the one or more video presentations.

BRIEF DESCRIPTION OF DRAWINGS
[0024] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such drawings includes the disclosure of electrical components, electronic components, or circuitry commonly used to implement such components.
[0025] FIG. 1 illustrates an example network architecture (100) for implementing a system (108) for interactive purchasing of one or more products, in accordance with an embodiment of the present disclosure.
[0026] FIG. 2 illustrates an example block diagram (200) of a system (108) for interactive purchasing of one or more products, in accordance with an embodiment of the present disclosure.
[0027] FIG. 3 illustrates an example flow diagram (300) implemented by the proposed system (108), in accordance with an embodiment of the present disclosure.
[0028] FIGs. 4A-4B illustrate example visual flow representations (400) implemented by the proposed system (108), in accordance with embodiments of the present disclosure.
[0029] FIG. 5 illustrates an example method flow diagram (500), implemented by the proposed system (108), in accordance with an embodiment of the present disclosure.
[0030] FIG. 6 illustrates an example computer system (600) in which or with which a proposed system (108) may be implemented, in accordance with an embodiment of the present disclosure.
[0031] The foregoing shall be more apparent from the following more detailed description of the disclosure.

DETAILED DESCRIPTION
[0032] In the following description, for explanation, various specific details are outlined in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0033] The ensuing description provides exemplary embodiments only and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.
[0034] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail to avoid obscuring the embodiments.
[0035] Also, it is noted that individual embodiments may be described as a process that is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[0036] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive like the term “comprising” as an open transition word without precluding any additional or other elements.
[0037] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0038] The terminology used herein is to describe particular embodiments only and is not intended to be limiting the disclosure. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any combinations of one or more of the associated listed items.
[0039] The present disclosure provides a system and a method that combines cutting-edge technologies to create an interactive personalized buying guide that harnesses a power of branching narratives and a generative artificial intelligence (AI). The system redefines the way users engage with e-commerce platforms by allowing the users to actively participate in shaping their product recommendations. Further, the system transforms these recommendations into dynamic video presentations that are more intuitive and engaging, while providing a personalized approach for breaking down technical jargons and selecting products that align with consumer preferences and requirements. The system bridges a gap between vast arrays of products available in the online marketplace and provides a personalized shopping experience that consumer’s desire, ultimately transforming the way consumers explore and engage with the e-commerce platforms.
[0040] The various embodiments throughout the disclosure will be explained in more detail with reference to FIGs. 1-6.
[0041] FIG. 1 illustrates an example network architecture (100) for implementing a system (108) for interactive purchasing of one or more products, in accordance with an embodiment of the present disclosure.
[0042] In an embodiment, the proposed system (108) may be referred as a system (108) or an intelligent system (108) throughout the disclosure. As illustrated in FIG. 1, one or more users (102-1, 102-2…102-N) may be connected to the system (108) through one or more computing devices (104-1, 104-2…104-N). Further, the one or more computing devices (104-1, 104-2…104-N) may be connected to the system (108) through a network (106). A person of ordinary skill in the art will understand that the one or more users (102-1, 102-2…102-N) may be collectively referred as the users (102) and individually referred as the user (102). One or more computing devices (104-1, 104-2…104-N) may collectively referred as the computing devices (104) and individually referred as the computing device (104).
[0043] In an embodiment, the computing devices (104) may include, but not be limited to, a mobile, a laptop, etc. Further, the computing devices (104) may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as a camera, an audio aid, a microphone, or a keyboard. Further, the computing devices (104) may include a mobile phone, a smartphone, virtual reality (VR) devices, augmented reality (AR) devices, a laptop, a general-purpose computer, a desktop, a personal digital assistant, a tablet computer, and a mainframe computer. Additionally, input devices for receiving input from the user (102) such as a touchpad, a touch-enabled screen, an electronic pen, and the like may be used.
[0044] In an embodiment, the network (106) may include, by way of example but not limitation, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. The network (106) may also include, by way of example but not limitation, one or more of a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public-Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, or some combination thereof.
[0045] In an embodiment, the system (108) may receive information from the users (102), where the information may be associated with a purchasing category selected by the users (102). For example, the users (102) may search/browse a page of an application associated with the system (108). The users (102) may be introduced to an interactive personalized shopping experience where a user-friendly interface may guide the users (102) through a series of questions designed to gather information about their preferences, needs, and requirements. The information may include but not limited to a product type, a budget range, and a brand preference associated with the purchasing category. Further, the system (108) may dynamically filter the information to generate one or more product recommendations.
[0046] In an embodiment, responses to the series of questions from the users (102) may be used as filters that narrow down a vast array of available products. Each response may correspond to a specific attribute or category relevant to the user's preferences. Further, the system (108) may use a sophisticated mapping system that may dynamically apply these filters to a product database, intelligently refining the available options based on the inputs provided by the users (102).
[0047] In an embodiment, the system (108) may generate, via an artificial intelligence (AI) engine, one or more product recommendations based on the information. The system (108) may utilize advanced generative AI algorithms to filter user data and generate personalized product recommendations. The system (108), via the AI engine, may analyze user's preferences and match them to relevant product features, specifications, and user reviews. The AI-generated recommendations may be presented in a product card based format, outlining key product details, benefits, and comparisons based on the user's specified filters.
[0048] Further, in an embodiment, the system (108) may generate one or more text-based recommendations associated with the one or more product recommendations. Further, the system (108) may visually represent the one or more text-based recommendations into one or more video presentations using the AI engine. The one or more video presentations may include, but not limited to, a clickable element that may enable the users (102) to interact and provide inputs to the system (108). To enhance user engagement, the one or more text-based recommendations may be seamlessly transformed into dynamic video presentations. A text-to-video generative AI model may be employed by the system (108) to convert the textual content into the one or more video presentations. The one or more video presentations may include, but not limited to, captivating visuals, animations, and voiceovers that effectively convey an essence of each recommended product.
[0049] In an embodiment, the AI engine may utilize Large Language Models (LLMs) to generate outputs. The LLMs may include a Few-Shot learning mechanism, where an existing model may learn new tasks with a few examples or instances. For example, the AI engine may use the LLM to generate the text-based recommendations and visually represent the one or more text-based recommendations into the one or more video presentations.
[0050] In an embodiment, the system (108) may dynamically update the one or more visually represented product recommendations based on one or more inputs provided by the users (102) in real-time and determine a progression of the one or more video presentations. For example, the users (102) may be presented with a personalized video guide, where the users (102) may interact with at least one clickable element embedded within the one or more video presentations/clips. Clicking on these elements may provide additional information, allowing the users (102) to make informed decisions. As the users (102) engage with the one or more video presentations, the system (108) may dynamically update the content based on their interactions, ensuring that the information remains current and relevant.
[0051] In an embodiment, the system (108) may generate an interactive video presentation that adapts in real-time as the users (102) explore different options and interact with the content. Further, decisions from the users (102) may lead to different outcomes or "endings" within the one or more video presentations, showcasing various sets of product recommendations based on different scenarios.
[0052] In an embodiment, the system (108) may secure personal data collected from the information with an utmost care and store the personal data securely. The personal data may be anonymized and used solely for generating tailored recommendations.
[0053] For example, in an embodiment, the system (108) may provide personalized and anonymous mental health support and coping strategies. The users (102) may answer questions related to their emotions, stressors, and coping preferences. The system (108) may generate audio and video guides with mindfulness exercises, relaxation techniques, and personalized advice from mental health professionals. Further, the system (108) may monitor patterns in replies, allowing for an early detection of potential mental health issues. This may enable timely intervention and prevent mental deterioration of the users (102). Further, in an embodiment, the system (108) may enhance the user (102) support and issue resolution. The system (108) may provide personalized business or career consulting where the users (102) may answer questions about their business goals, challenges, or career aspirations. The system (108) may generate audio and video guides with tailored advice, best practices, and recommended strategies based on the user (102) responses.
[0054] In an embodiment, the system (108) may be implemented with E-learning platforms, health and wellness applications, travel planning platforms, home improvement platforms, financial planning applications. Further, the system (108) may be implemented in an automotive industry, with fashion and style platforms, culinary applications, and job search platforms.
[0055] Although FIG. 1 shows exemplary components of the network architecture (100), in other embodiments, the network architecture (100) may include fewer components, different components, differently arranged components, or additional functional components than depicted in FIG. 1. Additionally, or alternatively, one or more components of the network architecture (100) may perform functions described as being performed by one or more other components of the network architecture (100).
[0056] FIG. 2 illustrates an example block diagram (200) of a system (108) for interactive purchasing of one or more products, in accordance with an embodiment of the present disclosure.
[0057] Referring to FIG. 2, the system (108) may comprise one or more processor(s) (202) that may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that process data based on operational instructions. Among other capabilities, the one or more processor(s) (202) may be configured to fetch and execute computer-readable instructions stored in a memory (204) of the system (108). The memory (204) may be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory (204) may comprise any non-transitory storage device including, for example, a volatile memory such as a random-access memory (RAM), or a non-volatile memory such as an erasable programmable read only memory (EPROM), a flash memory, and the like.
[0058] In an embodiment, the system (108) may include an interface(s) (206). The interface(s) (206) may comprise a variety of interfaces, for example, interfaces for data input and output (I/O) devices, storage devices, and the like. The interface(s) (206) may also provide a communication pathway for one or more components of the system (108). Examples of such components include, but are not limited to, processing engine(s) (208) and a database (210), where the processing engine(s) (208) may include, but not be limited to, a data ingestion engine (212) and other engine(s) (214). In an embodiment, the other engine(s) (214) may include, but not limited to, a data management engine, an input/output engine, and a notification engine.
[0059] In an embodiment, the processing engine(s) (208) may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) (208). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) (208) may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) (208) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) (208). In such examples, the system (108) may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system (108) and the processing resource. In other examples, the processing engine(s) (208) may be implemented by electronic circuitry.
[0060] In an embodiment, the processor (202) may receive information via the data ingestion engine (212). The processor (202) may receive the information from one or more users (102). The processor (202) may store the information in the database (210), where the information may be associated with a purchasing category selected by the users (102). Further, the processor (202) may dynamically filter the information to generate the one or more product recommendations.
[0061] In an embodiment, the processor (202) may generate, via an AI engine, one or more product recommendations based on the information. The processor (202) may utilize advanced generative AI algorithms to filter user data and generate personalized product recommendations.
[0062] Further, in an embodiment, the processor (202) may generate one or more text-based recommendations associated with the one or more product recommendations. Further, the processor (202) may visually represent the one or more text-based recommendations into one or more video presentations using the AI engine. The one or more video presentations may include, but not limited to, a clickable element that enables the one or more users (102) to interact and provide inputs to the system (108).
[0063] In an embodiment, the processor (202) may dynamically update the one or more visually represented product recommendations based on one or more inputs provided by the users (102) in real-time and determine a progression of the one or more video presentations.
[0064] In an embodiment, the processor (202) may generate an interactive video presentation that adapts in real-time as the users (102) explore different options and interact with the content. Further, decisions from the users (102) may lead to different outcomes or endings within the one or more video presentations, showcasing various sets of product recommendations based on different scenarios.
[0065] In an embodiment, the processor (202) may secure personal data collected from the information with an utmost care and store the personal data securely. The personal data may be anonymized and used solely for generating tailored recommendations.
[0066] FIG. 3 illustrates an example flow diagram (300) implemented by the proposed system (108), in accordance with an embodiment of the present disclosure.
[0067] As illustrated in FIG. 3, in an embodiment, the flow diagram (300) may include the following steps.
[0068] At step 302: The system (108) may receive an input. The input may contain information provided by the users (102). The information may be associated with a purchasing category selected by the users (102). Further, the system (108) may dynamically filter the information to intelligently refine available options based on the inputs of the user (102).
[0069] At step 304: The system (108) may use a recommendation engine to process the information.
[0070] At step 306: The system (108) may use an interference model for training user data generated by the processing of the information. Further, the system (108) may generate one or more text-based recommendations.
[0071] At step 308: The system (108) may use a text-to-video voice over model to visually represent the one or more text-based recommendations into one or more video presentations.
[0072] At step 310: The system (108) may provide text to text translation for the one or more text-based recommendations.
[0073] At step 312: The system (108) may provide feedback to a Search Page (SP) module to determine if the text to text translation is accurate.
[0074] At step 314: The system (108) may identify keywords from the text to text translation to generate checkpoints.
[0075] At step 316: The system (108) may embed the checkpoints into one or more video presentations that are presented to the users (102) during the interaction.
[0076] FIGs. 4A-4B illustrate example visual flow representations (400) implemented by the system (108), in accordance with embodiments of the present disclosure.
[0077] As illustrated in FIG. 4A, in an embodiment, the user (102) may interact with the system (108) and provide his preference for purchasing, for example, an air conditioner. The following steps may be performed by the system (108).
[0078] At step 402: The system (108) may process the information and provide a personalized video guide among the generated one or more video presentations. Further, the system (108) may provide at least one clickable element that provides additional information, allowing the users (102) to make informed decisions.
[0079] At step 404: The system (108) may provide options to the users (102) based on the information provided by the user (102).
[0080] At step 406: The system (108) may, based on the options selected by the users (102), provide a customized solution that may include a product with a specific configuration.
[0081] At step 408: The system (108) may enable the user (102) to provide inputs via the at least one clickable element and further assist to provide a personalized solution.
[0082] As illustrated in FIG. 4B, in an embodiment, the system (108) may further process the inputs provided by the user (102) using the following steps.
[0083] At step 410: Once the product is approved by the user (102), the system (108) may provide a rating for the product.
[0084] At step 412: The system (108) may present the product to the user (102).
[0085] At step 414: The system (108) may, based on a final approval from the user (102), generate the customized solution to the user (102). As the user (102) engages with the one or more video presentations, the system (108) may dynamically update the content based on user interactions, ensuring that the information remains up-to-date and relevant. Further, an interactive video presentation provided via the one or more video presentations may adapt in real-time as the user (102) explore different options and interacts with the content.
[0086] FIG. 5 illustrates an example method flow diagram (500), implemented by the proposed system (108), in accordance with an embodiment of the present disclosure.
[0087] In an embodiment, the method flow diagram (500) may include the following steps.
[0088] At step 502: The method may include receiving, by the system (108), information from one or more users (102), where the information may be associated with a purchasing category selected by one or more users (102).
[0089] At step 504: The method may include generating, by the system (108), via an AI engine, one or more product recommendations based on the information.
[0090] At step 506: The method may include visually representing, by the system (108), the one or more product recommendations.
[0091] At step 508: The method may include dynamically updating, by the system (108), the visually represented one or more product recommendations based on inputs provided by the one or more users (102).
[0092] FIG. 6 illustrates an exemplary computer system (600) in which or with which the proposed system (108) may be implemented, in accordance with an embodiment of the present disclosure.
[0093] As shown in FIG. 6, the computer system (600) may include an external storage device (610), a bus (620), a main memory (630), a read-only memory (640), a mass storage device (650), a communication port(s) (660), and a processor (670). A person skilled in the art will appreciate that the computer system (600) may include more than one processor and communication ports. The processor (670) may include various modules associated with embodiments of the present disclosure. The communication port(s) (660) may be any of an RS-232 port for use with a modem-based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fibre, a serial port, a parallel port, or other existing or future ports. The communication port(s) (660) may be chosen depending on a network, such as a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system (600) connects. The main memory (630) may be a Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. The read-only memory (640) may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chip for storing static information e.g., start-up or basic input/output system (BIOS) instructions for the processor (670). The mass storage device (650) may be any current or future mass storage solution, which can be used to store information and/or instructions.
[0094] The bus (620) may communicatively couple the processor (670) with the other memory, storage, and communication blocks. Optionally, operator and administrative interfaces, e.g., a display, keyboard, and cursor control device may also be coupled to the bus (620) to support direct operator interaction with the computer system (600). Other operator and administrative interfaces can be provided through network connections connected through the communication port(s) (660). In no way should the aforementioned exemplary computer system (600) limit the scope of the present disclosure.
[0095] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be implemented merely as illustrative of the disclosure and not as a limitation.

ADVANTAGES OF THE INVENTION
[0096] The present disclosure provides an intelligent system and a method for interactive purchasing of products, that seamlessly integrates various cutting-edge technologies such as generative artificial intelligence (AI) techniques and branching narratives.
[0097] The present disclosure provides an intelligent system that maps user responses to filters and dynamically applies these filters to a product database to efficiently handle large datasets and deliver real-time results.
[0098] The present disclosure provides an intelligent system that uses advanced generative AI algorithms that analyze user preferences and generate personalized recommendations.
[0099] The present disclosure provides an intelligent system that facilitates an interactive video presentation that is dynamically updated based on user interactions. A combination of programming, user experience design, and on-the-go stitching of generated videos is used to generate the interactive video presentation.
, Claims:1. A system (108) for interactive purchasing of one or more products, the system (108) comprising:
a processor (202); and
a memory (204) operatively coupled with the processor (202), the memory (204) storing instructions which, when executed, cause the processor (202) to:
receive information from one or more users (102), wherein the information is associated with a purchasing category selected by the one or more users (102);
generate, via an artificial intelligence (AI) engine, one or more product recommendations based on the information;
visually represent the one or more product recommendations; and
dynamically update the one or more visually represented product recommendations based on one or more inputs provided by the one or more users (102).

2. The system (108) as claimed in claim 1, wherein the processor (202) is to generate the one or more product recommendations by being configured to dynamically filter the information based on the purchasing category selected by the one or more users (102).

3. The system (108) as claimed in claim 1, wherein the information comprises at least one of: a product type, a budget range, and a brand preference associated with the purchasing category.

4. The system (108) as claimed in claim 1, wherein the processor (202) is to generate one or more text-based recommendations associated with the one or more product recommendations.

5. The system (108) as claimed in claim 4, wherein the processor (202) is to visually represent the one or more text-based recommendations into one or more video presentations using the AI engine.

6. The system (108) as claimed in claim 6, wherein the one or more video presentations comprise at least one clickable element that enables the one or more users (102) to interact and provide the one or more inputs to the system (108).

7. The system (108) as claimed in claim 4, wherein the processor (202) is to dynamically update the one or more visually represented product recommendations based on the one or more inputs provided by the one or more users (102) in real-time and determine a progression of the one or more video presentations.

8. A method (500) for interactive purchasing, the method (500) comprising:
receiving (502), by a processor, associated with a system (108), information from one or more users (102), wherein the information is associated with a purchasing category selected by the one or more users (102);
generating (504), by the processor (202), via an artificial intelligence (AI) engine, one or more product recommendations based on the information;
visually representing (506), by the processor (202), the one or more product recommendations; and
dynamically updating (508), by the processor (202), the one or more visually represented product recommendations based on one or more inputs provided by the one or more users (102).

9. The method as claimed in claim 8, comprising generating, by the processor (202), the one or more product recommendations by being configured to dynamically filter the information based on the purchasing category selected by the one or more users (102).
10. The method as claimed in claim 8, comprising generating, by the processor (202), one or more text-based recommendations associated with the one or more product recommendations.

11. The method as claimed in claim 10, comprising visually representing, by the processor (202), the one or more text-based recommendations into one or more video presentations using the AI engine.

12. The method as claimed in claim 11, wherein the one or more video presentations comprise at least one clickable element that enables the one or more users (102) to interact and provide the one or more inputs to the system (108).

13. The method as claimed in claim 8, comprising dynamically updating, by the processor (202), the visually represented one or more product recommendations based on the one or more inputs provided by the one or more users (102) in real-time and determining the progression of the one or more video presentations.