System and method for automated wish processing and execution

Abstract

The invention provides a computer-implemented method and system for automated wish processing and execution. In one embodiment, a method includes receiving user data including a user desire, and analyzing the user data using one or more algorithms to identify at least one operable solution corresponding to the user desire, based on the analysis, determining a user desire based on the at least one operable solution. Structured digital content is generated and output in a format configured for presentation on a user device. In this application, the user data may include preferences, behavioral patterns, market information, and associated classification details, the structured digital content may include, for example, execution plans, impact analyses, marketing analyses, or design templates, and the outputs may be adapted to be propagated through public networks, private groups, enterprise platforms, or other distribution channels.

Description

[0001] Cross-references to related applications

[0002] This application claims the benefit of U.S. Provisional Application No. 63 / 696,875, filed September 20, 2024. The contents of that application are incorporated herein by reference. Invention Field

[0003] The present invention relates generally to computer-implemented systems, and more particularly to computer-implemented systems and methods for automating processing, execution, and feedback integration. Background Technology

[0004] Modern computing platforms increasingly rely on automation to integrate user preferences, enterprise services, and marketplace interactions. However, existing systems often focus on narrow functions, such as task scheduling, content delivery, or e-commerce transactions, lacking a unified framework for translating individual or organizational goals into actionable outcomes.

[0005] A long-standing problem is that users often have broad or abstract goals, such as lifestyle improvement, health tracking, or launching new products, but traditional tools fail to provide a structured approach to translating these goals into actionable steps. Current applications tend to operate independently, requiring manual coordination across multiple platforms. This fragmentation increases complexity, delays execution, and limits scalability.

[0006] Another issue is that feedback and validation are often separate from execution. While some platforms offer user ratings or analytics, these mechanisms fail to achieve a closed loop by refining future execution or by integrating financing, voting, or competition mechanisms. Similarly, personal development aspects (such as logs, behavioral analytics, or health tracking) are handled by separate applications not integrated into a common execution framework.

[0007] Furthermore, traditional systems often raise concerns about transparency and trust. Many platforms rely on centralized operators to manage user data, leaving users with insufficient control. This hinders democratic verification of results and limits opportunities for equitable revenue sharing or secure record-keeping through distributed technologies.

[0008] Therefore, a comprehensive, computer-implemented system is needed that will enable end-to-end automation, reduce reliance on fragmented applications, and create a closed-loop architecture that translates expectations into executable, effective, and measurable results. Summary of the Invention

[0009] The implementation provides a computer-based method for automating wish processing and execution. It receives user data including user wishes and analyzes the user data using one or more algorithms to identify at least one actionable solution corresponding to the user wish. Based on the analysis, structured digital content is generated and output in a format configured for presentation on a user device.

[0010] This user data may include preferences, behavioral patterns, market information, and associated category details. The structured digital content may include, for example, execution plans, impact analyses, marketing analytics, or design templates. The output is adaptable for distribution through public networks, private groups, enterprise platforms, or other distribution channels.

[0011] In some aspects, user interaction and market response data can be analyzed to generate success metrics, such as engagement indicators, market fit results, or behavioral trends. These metrics can be used to refine subsequent implementation. Validation of workable solutions can be carried out through mechanisms including community voting, expert review, or market ranking, and in some cases, financial support or sponsorship can be enabled. The resulting content can be additionally stored in a blockchain ledger to ensure transparency and immutable record preservation.

[0012] In some respects, user desires can be linked to market platforms that support competition, financing, and the fair distribution of intellectual property or revenue. Personalized exploration features (including logging, assessments, health tracking, and progress monitoring) can also be incorporated, generating personalized insights or rewards to support overall user growth.

[0013] The implementation plan provides a corresponding system, which includes a memory for storing instructions and a processor for executing the instructions to perform the above operations.

[0014] To achieve the foregoing and related objectives, certain embodiments include features fully described below and specifically pointed out in the claims. The following description and drawings illustrate certain exemplary aspects of the embodiments in detail. However, these aspects indicate only a few of the various ways in which the principles of the embodiments may be employed, and this disclosure is intended to include all such aspects and their equivalents.

[0015] These and other objects of the invention will undoubtedly become apparent to those skilled in the art after reading the following detailed description of the preferred embodiments illustrated in the various figures. Attached Figure Description

[0016] Figure 1 An example of an automated processing and execution system based on the implementation plan is given.

[0017] Figure 2 Examples are given according to the implementation plan. Figure 1 The input interface for wishes.

[0018] Figure 3 Examples are given according to the implementation plan. Figure 1 The processor module.

[0019] Figure 4 Examples are given according to the implementation plan. Figure 1 The generator module.

[0020] Figure 5 Examples are given according to the implementation plan. Figure 1 Output and shared interfaces.

[0021] Figure 6 An example of an automated processing and execution system based on an alternative implementation scheme is shown.

[0022] Figure 7 Examples are given according to the implementation plan. Figure 6 The analyzer module.

[0023] Figure 8 Examples are given according to the implementation plan. Figure 6 The market connector system.

[0024] Figure 9 Examples are given according to the implementation plan. Figure 6 A personal exploration system.

[0025] Figure 10 A flowchart illustrating a computer-implemented method for automated processing and execution according to an implementation scheme is provided. Detailed Implementation

[0026] This disclosure provides a detailed description of various embodiments. While specific implementation details are presented herein to facilitate a thorough understanding of this disclosure, it will be apparent to those skilled in the art that the invention can be practiced without following all such details. In some cases, well-known effective methods, procedures, components, and circuits have been omitted from the exhaustive description to avoid obscuring this disclosure. It should be understood that, as set forth in this specification, the technical features described individually in relation to a single drawing may be implemented discretely or in combination with other features.

[0027] System Architecture

[0028] Figure 1An automated processing and execution system 10 according to an embodiment of the present invention is illustrated. System 10 is implemented in a computing environment and configured to transform user desires into structured output through a series of functional components. As shown, system 10 includes a desire input interface 100, a processor module 200, a generator module 300, and an output and sharing interface 400.

[0029] The wish input interface 100 allows users to input their wishes or goals into the system 10. The processor module 200 executes algorithms to analyze user data associated with the wishes. The generator module 300 creates structured digital content based on the analysis results. The output and sharing interface 400 presents the structured digital content in a format suitable for display or distribution on user devices.

[0030] In the illustrated implementation, components 100 to 400 provide the core framework for the automated processing and execution of system 10. Each component will be described in more detail in the following paragraphs.

[0031] Figure 2 An example of a wish input interface 100 according to an embodiment of the present invention is illustrated. The wish input interface 100 provides a structured input environment through which users can define wishes, goals, or objectives and submit them to an automated processing and execution system. In the illustrated embodiment, the wish input interface 100 includes personal wish input 101, corporate wish input 102, content and data categorization 103, activity and course matching 104, light and audio integration 105, and a philosophical framework 106.

[0032] The Personal Wish Input 101 captures a single user's aspirations or goals. Such goals may include health improvement, creative development, educational advancement, or lifestyle change. The Personal Wish Input 101 can be presented as a graphical user interface with optional fields, free text input, or guided prompts to help users clearly express their personal intentions.

[0033] The Enterprise Wish Input 102 can support organizational or business-related goals. Examples may include sustainability plans, product launches, market expansion, or talent development programs. Enterprise Wish Input 102 can accept structured data from enterprise systems or allow designated users to submit purposes aligned with company strategy.

[0034] Content and data classification 103 organizes received wishes into categories and hierarchies. This component can apply rules or machine learning algorithms to categorize wishes based on attributes such as topic, urgency, resource requirements, or feasibility. Classification enables the system to efficiently route inputs to appropriate processing and production paths.

[0035] Activity and course matching 104 associates submitted desires with actionable activities. For example, a desire to reduce stress can be matched with a meditation course, while a company goal focused on skills development can be matched with a training module. Activity and course matching 104 can use keyword matching, collaborative filtering, or semantic analysis to align user goals with available resources.

[0036] The light and audio integration 105 can provide optional enhancements to the user experience through multimodal input. For example, the system can generate audio tones, binaural beats, or light-based cues corresponding to the user's stated desires. Such integrations can support therapeutic, motivational, or immersive effects and also provide data points for further analysis of user engagement.

[0037] In some implementations, content and data classification 103 can be configured to receive and organize user-submitted information in various formats. Data may include, but is not limited to, text, images, videos, recordings, music files, or other multimedia formats. Classification can be based on metadata, semantic tags, or contextual attributes, allowing the system to flexibly handle both structured and unstructured input.

[0038] In contrast, the light and audio integration 105 can be tailored not only to data formats but also to the incorporation of sensory or frequency-based stimuli. In some implementations, visual light patterns, color frequencies, or video-derived luminance signals can be combined with audio or musical tones to create an immersive feedback environment.

[0039] Philosophical framework 106 establishes the conceptual foundation for the desire input interface. In some implementations, this framework may emphasize non-material outcomes, such as personal growth, community benefits, or sustainability impacts. By incorporating such a framework, the system can guide users in defining their desires holistically, rather than solely focusing on direct material outputs.

[0040] Components 101 to 106 together enable the wish input interface 100 to serve as a common input point for both individual and enterprise users. These components support structured input, intelligent categorization, activity association, experience enhancement, and conceptual consistency, thereby enabling a comprehensive approach to automating processing and execution cycles.

[0041] Figure 3 A processor module 200 according to an embodiment of the present invention is illustrated. The processor module 200 is responsible for analyzing user data, interpreting desires, and preparing operable outputs for subsequent generation. In the illustrated embodiment, the processor module 200 includes personnel data input 201, business data input 202, algorithm 203, behavior deconstruction 204, testing and verification 205, and a creator studio 206.

[0042] Personnel Data Input 201 collects and processes personal user information. This information may include demographic data, user preferences, behavioral history, psychological assessments, or health indicators. Personnel Data Input 201 normalizes heterogeneous data sources, enabling consistent subsequent analysis across multiple users.

[0043] In some implementations, personnel data input 201 may also include publicly available social media content, provided the user has consented to sharing such information with the system. Social media content may encompass posts, comments, likes, images, videos, or other publicly visible material. By incorporating this information, the system can analyze user behavior, preferences, interests, and expressed thoughts, as well as multimedia elements such as shared images or videos. This analysis enables a more comprehensive understanding of user characteristics and context, thereby improving the accuracy of actionable solution identification.

[0044] Business Data Input 202 collects organizational and market-oriented data. This may include business objectives, product specifications, market conditions, resource availability, or regulatory considerations. Business Data Input 202 enables the system to align the aspirations of a user or business with the broader strategic and business context.

[0045] Algorithm 203 can be used to process user and business data in a transparent and adaptive manner. Such algorithms may include clustering, classification, recommendation, and semantic analysis. Because the algorithms can be open source, they can be updated, audited, or extended by external contributors, thereby ensuring fairness, transparency, and adaptability in the analysis process.

[0046] In some implementations, algorithm 203 may include a multidimensional mental mapping algorithm designed to categorize user responses into different philosophical types and assess compatibility between individuals. The algorithm may employ a multidimensional classification model utilizing a rating matrix to map individual responses to philosophical categories. In one specific implementation, the assessment may include various items, each with multiple response options corresponding to philosophical frameworks such as Platonic fusion, existential freedom, idealistic transcendence, Proustian temporality, psychoanalysis, and critical deconstruction. The assessment design may follow a balanced distribution matrix to ensure equal representation of each philosophical type in the problem domain. Each response option may be philosophically validated against established academic literature to maintain theoretical authenticity, and semantic embedding techniques may be used to map each option to a philosophical type based on an expert-validated conceptual framework.

[0047] In some implementations, the compatibility engine can also implement a symmetric matrix structure to store pre-computed coefficients for pairwise combinations of philosophical types. Compatibility can be determined by combining philosophical opposition analysis, complementarity assessment, and potential conflict assessment. For example, high compatibility (e.g., a score between 0.8 and 1.0) may reflect synergy, medium compatibility (0.4 to 0.7) may reflect feasible differences, and low compatibility (0.0 to 0.3) may reflect fundamental conflict.

[0048] In some implementations, algorithm 203 may also include dynamic content generation, an open-source model, and a personalization engine. This engine can combine primary type characteristics with secondary type modifiers using a weighted influence model (e.g., 70% from primary type and 30% from secondary type). A rule-based natural language generation system can be used to generate narrative reports, predictions, and book recommendations consistent with philosophical similarity matching. In some implementations, curated reading lists can be derived through academic citation analysis and topic scoring.

[0049] Behavioral deconstruction 204 breaks down user desires into measurable components. For example, desires can be analyzed along dimensions such as feasibility, engagement, and impact, which can be expressed as coordinates or variables in a multidimensional framework. This allows the system to represent abstract objectives in a structured and quantifiable form.

[0050] Testing and validation 205 allows for the evaluation of the initial output before it is passed on to subsequent modules. Testing may involve simulation, A / B comparison, or expert review, while validation may involve user feedback or system benchmarking. This component ensures that the identified operational solution meets reliability, accuracy, and relevance thresholds.

[0051] Creator Studio 206 provides tools for generating intermediate outputs, refining or customizing them. Users or businesses can use Creator Studio 206 to design content, adjust parameters, or integrate external data. In some implementations, Creator Studio 206 may include AI-assisted content generation, enabling the rapid creation of report drafts, summaries, or media elements linked to user preferences.

[0052] In some implementations, Creator Studio 206 provides an environment for content creation and editing. Creator Studio 206 supports a variety of input and output formats, including audio, video, text, images, and other multimedia data. Creator Studio 206 can be implemented as a web-based platform, mobile application, or desktop environment and can be configured to enable users to upload, edit, annotate, or generate content using integrated tools. In some implementations, Creator Studio 206 may also interface with Algorithm 203 to apply automated processing (such as recommendation, enhancement, or formatting), allowing both manual and algorithm-assisted content generation. Components 201 through 206 together enable Processor Module 200 to transform diverse user and enterprise inputs into structured, validated, and readily available data. This processed data can then be provided to the Generator Module for the creation of structured digital content in subsequent stages of the system.

[0053] Figure 4 A generator module 300 according to an embodiment of the present invention is illustrated. The generator module 300 can generate structured digital content based on data processed by a processor module. In the illustrated embodiment, the generator module 300 may include a wish execution plan report 301, an impact analysis report 302, a marketing analysis report 303, a design template 304, and a SaaS integration 305.

[0054] The Wish Implementation Plan Report 301 provides step-by-step guidance for achieving a user's wish. Such reports may include milestones, recommended resources, timelines, and task assignments. In some implementations, the Implementation Plan Report 301 may be dynamically updated in response to additional data or feedback.

[0055] Impact Analysis Report 302 assesses the potential and outcomes of an action to be carried out. The assessment may involve individual progress, business benefits, environmental impact, or social impact. Impact Analysis Report 302 may incorporate quantitative measures, qualitative assessments, or a combination of both to provide a comprehensive view of the results.

[0056] When the intention involves corporate or business objectives, a Marketing Analysis Report 303 may be generated. This report may provide insights into market positioning, audience targeting, competitive landscape, or revenue opportunities. A Marketing Analysis Report 303 can help businesses launch new initiatives or validate proposed strategies against market data.

[0057] Design template 304 provides a pre-structured visual or text framework for presenting results. Templates may include slides, infographics, workflow diagrams, or interactive dashboards. Users or businesses can adapt design template 304 to customize the communication of deliverables while maintaining consistency and efficiency.

[0058] SaaS Integration 305 allows the generator module 300 to interact with external Software-as-a-Service platforms. Examples include project management tools, customer relationship management systems, education platforms, or financial applications. Through SaaS Integration 305, the generated content can be automatically delivered to external systems for further use, execution, or monitoring.

[0059] Components 301 to 305 together enable generator module 300 to transform processed data into tangible and adaptable outputs. These outputs can be delivered to output and shared interfaces for presentation or dissemination across various channels.

[0060] Figure 5 An output and sharing interface 400 according to an embodiment of the present invention is illustrated. The output and sharing interface 400 can present structured digital content generated by the system in a format suitable for user consumption or dissemination. In the illustrated embodiment, the output and sharing interface 400 may include a public channel 401, a private group 402, and an enterprise network 403.

[0061] Public channels 401 provide mechanisms for publicly distributing generated content to a broad audience. Examples include social media platforms, public websites, or newsletters. Public channels 401 allow users to share deliverables such as executive reports, analyses, or creative works for the community to view, discuss, or verify.

[0062] In some implementations, public channel 401 may also include a referral and link-sharing system that incorporates multi-layered attribute and password verification. Each referral link may embed a unique identifier generated by the system and cryptographically associated with the referring account. When a downstream user activates a referral link, attribute data can be recorded via server-side logging, device fingerprinting, or blockchain-based timestamps. In some specific implementations, asymmetric encryption can be used to encode the identifier, where a private key signs the referral data and a public key is used for verification by the merchant server before granting benefits to the referrer. This encryption scheme ensures that referral records are tamper-proof, verifiable, and fraud-proof. To support large-scale deployment, probabilistic data structures can be used to correlate referral clicks with conversion events under high-traffic conditions.

[0063] Revenue-sharing logic associated with Public Channels 401 can be implemented through a dynamic payment mechanism that automatically distributes revenue among stakeholders. For example, when a product or template is purchased through a referral link, the system can allocate revenue so that the original creator receives the primary share (e.g., 60%), the referrer receives a secondary share (e.g., 10%), and the remainder is distributed to the platform operator or service provider. In some implementations, the payment weights can be dynamically adjusted based on behavioral metrics such as engagement time, repeat purchases, or the referrer's community ranking. Private Groups 402 allow for the controlled sharing of generated content within a limited set of users. These groups can include family, friends, teams, or collaborators and can be managed through access permissions. Private Groups 402 can be useful when sensitive content needs to be shared selectively, or when collaborative review is desired before wider distribution.

[0064] Enterprise Network 403 enables the dissemination of structured digital content within professional or organizational environments. For example, Enterprise Network 403 can distribute project plans, marketing reports, or training modules to internal employees or external partners. Enterprise Network 403 can also integrate with company systems, such as project management tools or customer relationship platforms, to ensure that the resulting outputs are consistent with ongoing operations.

[0065] Sub-components 401 through 403 together enable the output and shared interface 400 to provide flexible dissemination paths tailored to the intended audience. Content can be directed outward to public platforms, selectively to private groups, or strategically within enterprise systems, thereby translating user desires into actionable and communicable results.

[0066] Figure 6 An automated processing and execution system 20 according to an alternative embodiment of the present invention is illustrated. In this embodiment, system 20 may include components of the previously described wish input interface 100, processor module 200, generator module 300, and output and sharing interface 400. Additionally, system 20 may also include an analyzer module 500, a market connector system 600, and a personal exploration system 700.

[0067] The analyzer module 500 provides functionality for monitoring outcomes associated with generated digital content and user interactions. This module supports performance evaluation, generation of success metrics, and identification of behavioral patterns for granular targeting of subsequent execution.

[0068] The Market Connector System 600 extends the system to the community and business levels. This component supports user desire validation, competitive ranking, expert or community review, crowdfunding, and transparent revenue sharing. By integrating these features, the Market Connector System 600 enables selected desires to move from planning to execution with external participation and support.

[0069] The Personal Exploration System 700 can complement aspiration execution by leveraging the user's focus on growth and self-development. This component supports logging, assessment, health tracking, and educational or coaching activities, enabling users to monitor their mental, psychological, and physical progress in conjunction with their aspirations.

[0070] Figure 7 An analyzer module 500 according to an embodiment of the present invention is illustrated. The analyzer module 500 is responsible for monitoring, interpreting, and evaluating results associated with the generation and dissemination of digital content within an automated processing and execution system. In the illustrated embodiment, the analyzer module 500 may include engagement metrics 501, market fit analysis 502, behavioral patterns 503, and influence and impact 504.

[0071] Engagement metric 501 tracks how users interact with structured digital content generated by the system. Such metrics can include views, completion rates, engagement levels, or interaction frequency. Engagement metric 501 allows systems to measure user engagement and provides quantitative evidence of desired adoption.

[0072] Market fit analysis 502 assesses how well the resulting outputs align with market needs or expectations. This analysis may include sales data, user surveys, or expert evaluations. In a business environment, market fit analysis 502 can be used to determine the commercial feasibility of pursuing a desired outcome, such as the acceptance of the proposed product or service.

[0073] Behavioral patterns 503 identify trends or reactions exhibited by users during or after exposure to content. These patterns may involve psychological responses, emotions, or decision-making tendencies. Behavioral patterns 503 can be analyzed over time to reveal insights into user motivations or adopted behaviors.

[0074] Impact and Influence 504 measures the extended outcomes of desired actions, not just immediate user interactions. For example, this component can consider community benefits, environmental contributions, or secondary effects such as knowledge sharing or carbon reduction. Impact and Influence 504 can combine quantitative and qualitative factors to provide a holistic view of outcomes.

[0075] The analyzer module 500 enables iterative refinement of subsequent wish processing and execution, thereby ensuring continuous improvement and adaptation to user and market environments.

[0076] Figure 8A market connector system 600 according to an embodiment of the present invention is illustrated. The market connector system 600 provides mechanisms for validating, financing, and scaling support for user desires in a broader community or market environment. In the illustrated embodiment, the market connector system 600 may include a product / service input 601, a market platform 602, a competition processor 603, funding and decision-making 604, cash flow tracking 605, and IP and revenue sharing 606.

[0077] Product / Service Input 601 allows users or businesses to describe product, service, or project concepts corresponding to their submitted desires. Product / Service Input 601 accepts structured data describing specifications, objectives, and resource requirements.

[0078] Marketplace 602 displays submitted wishes or supplies in a format visible to other participants. Lists may include descriptions, deadlines, budgets, or ranking criteria. Marketplace 602 provides transparency and accessibility, enabling community members or stakeholders to evaluate available options.

[0079] The Contest Processor 603 allows wishes or projects to be ranked or compared through community voting, expert review, or algorithmic scoring. The Contest Processor 603 supports contests, leaderboards, or challenge-based formats, thereby encouraging high-quality submissions and democratic selection.

[0080] Funding and Decisions 604 can provide a mechanism for allocating resources to selected aspirations. This can include crowdfunding campaigns, investor commitments, or institutional sponsorship. Funding and Decisions 604 can further record the results of voting or reviews and then translate them into actionable financial or organizational commitments.

[0081] Cash flow tracking 605 monitors the allocation of funds associated with the execution of aspirations. Cash flow tracking 605 can include transparent reporting of inflows, expenditures, and balances, thereby ensuring accountability and credibility within the system.

[0082] IP and Revenue Sharing 606 provides automated mechanisms for allocating intellectual property or revenue generated by the desired outcome. This may include smart contracts, licensing frameworks, or tokenized ownership models. By achieving equitable sharing, IP and Revenue Sharing 606 fosters collaboration and encourages participation.

[0083] Components 601 to 606 allow the Market Connector System 600 to integrate validation, financing, and accountability into automated processing and execution systems. This transforms abstract aspirations into actionable projects supported by community input, expert review, and transparent financial mechanisms.

[0084] Figure 9A personal exploration system 700 according to an embodiment of the present invention is illustrated. The personal exploration system 700 enables users to monitor and develop mental, intellectual, and physical growth by combining the execution of desires. In the illustrated embodiment, the personal exploration system 700 may include a log and dream record 701, a personal page 702, testing and analysis 703, learning and growth 704, health and wellness 705, and tokenized sharing 706.

[0085] The journal and dream log 701 provides users with a digital space to record personal reflections, goals, or dream narratives. These entries serve as qualitative data for self-discovery and can be referenced in subsequent user growth analysis.

[0086] Personal page 702 can present a customized information flow or dashboard summarizing the user's aspirations, progress, and related insights. Personal page 702 can aggregate output from other modules to provide users with a coherent view of their ongoing developments.

[0087] The Test and Analysis 703 allows users to complete assessments such as psychological profiles, behavioral surveys, or skills evaluations. The results can be analyzed to generate feedback that can guide future desired inputs or refine system recommendations.

[0088] Learning and Growth 704 offers educational and developmental resources. Examples include courses, mentorship programs, interactive workshops, or reading materials. Learning and Growth 704 is designed to align with users' aspirations to encourage skills development and holistic improvement.

[0089] Health and Wellness 705 supports tracking physical and mental well-being. This can include monitoring exercise, diet, mindfulness practice, or stress management. Health and Wellness 705 can generate recommendations or alerts to support a user's overall balance and productivity.

[0090] Tokenized Sharing 706 allows users to receive recognition or rewards for their contributions to the system. This can include issuing tokens for log entries, completed activities, or collaborative input. Tokenized Sharing 706 fosters community engagement and incentivizes long-term participation.

[0091] Components 701 to 706 allow the Personal Exploration System 700 to extend the automated processing and execution system beyond transaction results, thereby promoting the user's continued personal growth and well-being.

[0092] Structure for wish assessment

[0093] In some implementations, automated processing and execution systems (e.g., system 10 or 20) may employ a structured framework to evaluate user-submitted wishes or projects. This framework may include categorization tables and multi-step decision-making processes, enabling transparent and systematic progress from input to market launch.

[0094] For example, each submitted wish can be evaluated using three main coordinates:

[0095]

[0096] An automated processing and execution system can normalize each coordinate into a number or categorical score. This classification can then be used in a three-dimensional evaluation space to compare different desires or items.

[0097] In operation, users first submit wishes or projects through a wish input interface, providing descriptive information, goals, and any relevant resource data. The system then analyzes the submission based on three coordinate assignment values—feasibility, engagement, and impact—generating an X, Y, Z representation of the wish. Based on these coordinates, the algorithm matches the wish with suitable resources, collaborators, or opportunities. Once matched, the system generates a structured digital plan, including milestones, timelines, and recommended actions. In some implementations, the system can also initiate automated execution of the plan by sending notifications or execution requests to relevant collaborators, businesses, or APIs. For example, in the case of a film production wish, the system can automatically notify screenwriters, directors, producers, actors, sound engineers, and marketing agents to begin the assigned tasks, while also triggering automated processes such as digital contract signing, financial settlement, or logistical coordination through connected systems. Users can monitor execution progress through the interface and ultimately receive completed outputs, such as a finished video, which can also be automatically published to designated accounts or platforms. After execution, the wish or project can be reviewed by community members and domain experts, who may validate the project through voting, ranking, or comments. Once a project has been fully validated and resource-allocated, it can be released to the marketplace, where its performance can be monitored and the results can be fed back to the analyzer module for continuous refinement.

[0098] Technology stack and integration

[0099] In some implementations, automated processing and execution systems (e.g., automated processing and execution systems 10 or 20) can operate on a multi-tiered technology stack designed for scalability and interoperability. The infrastructure layer may include cloud computing resources providing storage, networking, and resilient processing capabilities. The artificial intelligence layer performs natural language processing, behavioral analysis, and recommendation matching to support classification and plan generation. A blockchain layer can be integrated to ensure transparency, immutability, and traceability of transactions, voting results, or revenue sharing. The Internet of Things (IoT) layer connects to external devices, sensors, or enterprise systems to provide real-time contextual data. The virtual and augmented reality layer can optionally provide immersive experiences for training, healthcare activities, or visualization of desired outcomes. These layers are coordinated through standardized APIs and middleware, enabling seamless integration with external platforms such as Software as a Service (SaaS) applications, enterprise resource planning (ERP) systems, and third-party marketplaces. By adopting this stack, the system provides a scalable, modular framework that supports end-to-end automation while remaining adaptable across diverse user and enterprise environments.

[0100] Use cases and applications

[0101] In some implementations, automated processing and execution systems can be applied across both personal and enterprise environments to demonstrate the breadth of their functionality. For example, in a personal use case, a user might submit a desire to reduce stress. The system can analyze the input, categorizing it according to dimensions of feasibility, engagement, and impact, and then generate a structured execution plan that could include a 30-day mindfulness course, daily log prompts, and wellness tracking via a personal exploration system. The system can then further automate the execution of the plan's elements, prompting the user to confirm attendance, and in the case of a yoga class, once agreed to or paid for, the system can automatically add the class to the user's calendar, book a spot with the yoga provider, and generate any necessary booking confirmations. Thus, the user can attend the event directly without manual scheduling. Progress can then be measured using engagement metrics and wellness indicators, and the collected feedback can reinforce subsequent improvements.

[0102] In the enterprise use case, companies can submit their desire to launch sustainable products. The system can evaluate projects based on resource requirements and market impact, and then generate a structured execution plan, including procurement strategies, supply chain milestones, and anticipated carbon reduction metrics. The system can also initiate automated execution, automatically sending purchase orders to certified suppliers, arranging logistics through an integrated transportation platform, and generating draft contracts for supplier execution. The system can also trigger marketing workflows by automatically booking advertising slots, distributing promotional content across enterprise channels, or reserving event spaces for product demonstrations. Companies can monitor execution progress through dashboards, while community and expert validation in the marketplace can further provide voting, ranking, or sponsorship opportunities. Once successfully completed, the product can be directly launched to marketplace channels, tracking results and feeding them back to the analytics module for refinement.

[0103] Market Function

[0104] In some implementations, automated processing and execution systems (e.g., System 10 or 20) may include a market framework integrating multiple forms of evaluation, competition, and trading. The market may incorporate evaluation reports, competition mechanisms, and gold flow trading, enabling the ranking and validation of submitted items or content. Rankings may reflect different dimensions; for example, strategy market rankings highlight the efficiency and cost of strategy execution, or music rankings in a content market reflect popularity, audience characteristics, and energy frequency analysis. The market can support products, services, events, strategies, design templates, currencies, and creative content in a unified environment. Business-oriented behaviors may include software, applications, services, products, and events, while lifestyle behaviors may include adopting solutions and equipment that improve daily efficiency, such as home appliances or local storage alternatives. The market may also support currency exchange across fiat currencies, virtual currencies, and goods, including secondhand items or digital assets such as non-fungible tokens, while content exchange can extend to games, newsletters, movies, music, and other creative works.

[0105] In some implementations, constraints can be imposed to improve efficiency and ensure the quality of interaction. Such constraints may include limiting partner SaaS software from excluding ads, pop-ups, or unnecessary login requests; allowing users to filter out unwanted content such as negative posts; and requiring merchants to adhere to topic restrictions, such as offering only environmentally friendly or recycled products. Through these mechanisms, the marketplace can provide a transparent and adaptive environment that validates user desires, supports competition, facilitates secure financial transactions, and aligns with user values ​​and preferences.

[0106] Technical processes and user procedures

[0107] In some implementations, automated processing and execution systems (e.g., System 10 or 20) enable technological processes that integrate AI and IoT technologies for adaptive automation. Sensors, wearables, and environmental monitors collect data on occupancy rates, air quality, noise levels, and user activity, while machine learning algorithms analyze this data to predict demand, optimize schedules, and personalize experiences. An automation engine generates intelligent triggers to adjust environmental variables, such as lighting, music, temperature, and notifications, based on time of day, user preferences, or task requirements. The system also supports personalization through user profiles that store individual preferences for workplace conditions, including music, lighting, temperature, and break schedules. Based on the detected task type (such as coding, design, or writing), the system can adapt to the surrounding environment by adjusting display brightness, soundscape, or focus assist, while wearables and desktop sensors monitor posture, stress levels, and activity to provide real-time recommendations for health and well-being.

[0108] In some implementations, food and nutrition automation can be incorporated. Networked kitchen appliances and automated machines can prepare customized meals based on dietary needs, while artificial intelligence can match food orders with local restaurants optimized for speed, cost, and dietary constraints. Calorie intake and medication adherence can be supported by automatically scanning meals and reminding users to order medications. The system can also provide event and entertainment management by automatically allocating space for activities such as music clubs, reading groups, or seminars and by configuring the environment accordingly. Virtual reality and augmented reality features can enhance these activities by enabling immersive collaboration, training, or participation across distributed locations. Sustainability optimizations can also be integrated, where heat exchange systems can reuse heat from data centers to heat offices or water, while smart lighting and climate control can adapt to occupancy and natural light conditions, thereby reducing energy consumption and improving environmental efficiency.

[0109] In some implementations, automated processing and execution systems (e.g., System 10 or 20) enable technological processes for the creation, distribution, and monetization of digital content. Creators such as musicians, artists, and filmmakers can create works including music, videos, art, or films, and then upload these works to platforms for tokenization, uploading, or streaming. Artificial intelligence tools can assist in editing, enhancing, and optimizing, including preparing for augmented, virtual, or mixed reality environments. Distribution and monetization can occur through various channels, including: NFT minting utilizing smart contracts that define royalties, licensing, and resale; subscription or pay-per-view models; and brand sponsorships or advertising that share revenue with creators. The system can also enable avatar-based interaction by providing immersive experiences through content delivery in AR, VR, or MR formats, and support live streaming with features such as real-time audience engagement (e.g., chat, gifting, and voting). Integration with Web3 infrastructure can include token-gated access to exclusive content or events, decentralized storage for secure and permanent custody, and automated financial transactions via blockchain. Audience engagement can be increased through behavioral tracking for personalized recommendations, gamification based on token rewards, and community features including forums, live Q&A, and collaborative projects.

[0110] In some implementations, user programs can be tailored to different stakeholders. Creators can register, create profiles linked to digital wallets, upload and tokenize content, set monetization terms, promote their work across platforms, and monitor revenue and analytics. Audiences can create accounts, configure avatars and preferences, connect wallets, discover and purchase content or NFTs, participate in live or immersive events, and receive referral and engagement rewards. Brands and sponsors can collaborate with co-branded content creators to run targeted advertising or sponsorship campaigns, distribute promotions to platform users, and track campaign performance through analytics dashboards. Overall, this process establishes a comprehensive ecosystem that leverages AR / VR technologies, avatars, NFTs, and Web3 infrastructure to empower creators, engage audiences, and sustain the digital economy.

[0111] In some implementations, automated processing and execution systems (e.g., System 10 or 20) can support user programs for employees and employers in a smart office environment. For employees, the onboarding process may include downloading a smart office app, creating a profile with work preferences, health goals, and dietary needs, and connecting wearable devices for health tracking. In daily workflows, the system can automatically adjust workspace conditions such as lighting, temperature, and music, while a smart calendar manages tasks, meetings, and breaks, and focus modes provide deep work playlists or immersive virtual workspaces. Health and wellness support may include real-time suggestions for posture, hydration, and screen breaks, guided meditation or yoga classes, and automated food ordering with calorie and medication tracking. Collaboration and activities can be facilitated through meeting room bookings that support automatically adjusted audiovisual settings and personalized settings for clubs or workshops. At the end of the day, employees can view productivity and wellness statistics, schedule tasks, and set preferences for the next day.

[0112] For employers and facilities managers, the system enables the deployment of office infrastructure through the installation of sensors, smart devices, and IoT hubs; and integration with human resources and wellness programs for data synchronization. Monitoring and optimization can be achieved through dashboards tracking office usage, energy consumption, and employee well-being, with AI-driven policy recommendations. Event and workshop management can include the automated scheduling of team-building activities, training courses, and recreational events, as well as the promotion of health initiatives. The system can also generate sustainability reports covering energy conservation, carbon footprint, and employee satisfaction, which can be shared with stakeholders on environmental, social, and governance compliance. Data privacy and security can be supported by encryption protocols and regulatory compliance measures, including GDPR and local standards. Expected outcomes can include quantifiable improvements in productivity, employee satisfaction, energy efficiency, health and well-being, and collaboration.

[0113] Specific implementation

[0114] In some implementations, automated processing and execution systems (e.g., System 10 or 20) provide complete solutions to address the technical challenges associated with integration with multi-functional service providers and cross-platform APIs. These systems connect business networks across industries, optimize the execution performance of triggers and actions in business workflows, and ensure the stability of data processing. Technical solutions may involve load control of data triggers, deduplication techniques, distributed processing, and optimized use of REST callback mechanisms. Overall, these specific implementations improve efficiency, reduce redundant operations, and enhance the reliability of workflow automation.

[0115] In some implementations, the design and load control of data triggers can be optimized. Triggers represent the initial step of a workflow and are responsible for retrieving data from the integrated application and initiating execution. The system can improve this process by segmenting data, dynamically filtering records, and customizing data flow according to different scenarios. For example, in test mode, compressed sample data can be returned, while in operational mode, API-based filters (such as date or ID) can be applied to control the amount of data. This load control mechanism reduces system stress and enables faster response times in real-time applications.

[0116] In some implementations, deduplication techniques can be applied to avoid redundant operations on the same data. During each triggered startup, the system can automatically create a deduplication table, filter historical data, and retain only unique identifiers. This method prevents unnecessary duplicate actions, reduces data transmission pressure, and enables more efficient workflow initialization. The deduplication mechanism can employ a lightweight indexing scheme or hash-based identifiers to ensure minimal overhead and high accuracy.

[0117] In some implementations, REST callback triggers can be optimized to improve the efficiency of instant notifications. REST callback functionality allows the system to deliver notifications as data changes, which is particularly useful in scenarios requiring frequent updates or real-time synchronization. To reduce load, the system can employ a dehydration and rehydration mechanism, whereby the initial notification sends only a simplified summary of the data. When additional details are needed, the dehydrated pointer can be used to retrieve the complete data on demand. This phased delivery alleviates the burden on the network and ensures that only the necessary data is delivered at any given time.

[0118] The system can also include diverse API filtering, supporting conditions such as date, ID, or field-based selection, thereby reducing unnecessary sending and improving performance across heterogeneous platforms. This technology framework can be deployed across multiple integration environments, including but not limited to browser extensions, applications, web applications, open-source connectors, and commercial ecosystems. Through these implementations, the present invention provides a comprehensive solution that can be integrated with enterprise applications, team workflows, and consumer-facing services.

[0119] In some implementations, the system can further support a classification and evaluation process that quantifies both tangible and intangible factors. For example, a dichotomy-based classification engine can be applied to divide events into progressively smaller categories, each associated with parameters such as cost, time, advantages (z1), and disadvantages (z2). The calculation engine can process the classification hierarchy (n), coordinate definitions (X, Y), and additional subcategories (An, Bn, Cn) to generate tokenized values ​​representing trade-offs under varying conditions. These tokens can capture the results using both quantifiable units (e.g., time, money, materials) and non-quantifiable units (e.g., energy, light, influence, or social impact). These tokens can be visualized along coordinate axes and incorporated into decision structures such as decision tables, enabling transparent and comparative evaluation of projects, strategies, or user desires.

[0120] Through these specific implementation methods, automated processing and execution systems can ensure intelligent load control, prevent redundant actions, simplify notifications, and provide a flexible framework for evaluating both material and non-material contributions within automated workflows.

[0121] Method Flowchart

[0122] Figure 10 A flowchart illustrating a computer-implemented method 1000 for automated processing and execution according to an embodiment is provided. Method 1000 includes the following steps:

[0123] S1002: Receive user data including user wishes;

[0124] S1004: Analyze user data using one or more algorithms to identify at least one actionable solution corresponding to the user's desire;

[0125] S1006: Generating structured digital content based on analyzed data; and

[0126] S1008: Output structured digital content in a format configured for presentation on user devices.

[0127] At step S1002, user data including user desires is received. User data may include information related to personal or corporate purposes, classification parameters, and contextual preferences, and may also include behavioral records or historical activity logs. The received data may be preprocessed or normalized to facilitate subsequent operations.

[0128] In step S1004, user data is analyzed using one or more algorithms to identify at least one actionable solution corresponding to the user's desire. This analysis may be performed by applying statistical models, machine learning processes, or semantic matching engines, and may consider feasibility, engagement, and influencing factors. During this step, available resources or collaborators may be matched with the user's desire.

[0129] In step S1006, structured digital content is generated based on the analyzed data. The generated content may include execution plans, analysis reports, design templates, or other structured outputs suitable for guiding the specific implementation of an actionable solution. In some implementations, templates may be automatically selected, and connectivity to external systems may be utilized to enhance the output.

[0130] In step S1008, the structured digital content is output in a format configured for presentation on the user's device. This output can be displayed on web platforms, mobile applications, or enterprise dashboards, and can also be distributed via public networks, private groups, or enterprise channels. Formatting and compatibility adjustments can be applied to ensure accurate and efficient presentation.

[0131] In some implementations, user interaction and market response data can be analyzed to generate success metrics, which provide both quantitative and qualitative assessments of outcomes associated with user desires. Success metrics may encompass engagement metrics (such as pageviews, engagement rates, completion levels, and interaction frequency) and market fit metrics (such as adoption trends, sales figures, or expert ratings). These metrics can be processed using statistical models or machine learning algorithms to identify behavioral patterns, predict future performance, and highlight areas for improvement. The resulting success metrics can then be applied to refine subsequent execution by adjusting resource allocation, modifying content formatting, or customizing recommendations to better align with user needs and market demands.

[0132] In other implementations, a workable solution can be validated through mechanisms that provide transparency and collective input. Community voting can be conducted to obtain feasibility or desirability assessments, expert reviews can be performed to evaluate technical or commercial viability, and market rankings can be applied to rank projects based on efficiency, cost, or popularity criteria. Validation results can serve as prerequisites for project progress, and in some cases, the validation process can facilitate direct financing or sponsorship. For example, projects that achieve good rankings or expert endorsements may enter into crowdfunding campaigns, institutional investment, or brand-backed sponsorships, thus linking validation results to financial support.

[0133] Additionally, personal exploration activities can be incorporated to support long-term user growth while fulfilling aspirations. Log modules can be used to record reflections and progress, performance assessments can provide behavioral or psychological insights, and health tracking tools can monitor posture, stress levels, exercise, or mindfulness activities. Personalized insights or tokenized rewards can be generated based on these activities, creating a closed-loop feedback system that supports aspiration fulfillment while promoting spiritual, psychological, and physical development. By integrating such activities with automated execution and community engagement, a holistic framework can be established that connects technological automation with user-centric growth and engagement.

[0134] Through these steps, user desires can be systematically received, analyzed, and transformed into structured outputs, presented in an executable and disseminable manner. This transformation of user desires into structured outputs simultaneously enables validation, funding, feedback integration, and overall development.

[0135] Specific implementation

[0136] In some implementations, the automated processing and execution system (e.g., system 10 or 20) may be implemented using hardware, firmware, software, or any combination thereof. The specific implementation may depend on the intended application and associated design constraints. Hardware used for such implementations may include, but is not limited to, central processing units (CPUs), graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), programmable logic devices (PLDs), gate logic, discrete components, or combinations thereof configured to perform the described functions. General-purpose processors may include microprocessors, controllers, microcontrollers or state machines, or combinations such as digital signal processors combined with microprocessors. In some cases, the process may be executed by specific functional circuitry optimized for performance, efficiency, or cost. Hardware selection may depend on application requirements, including speed, power consumption, cost, and physical size constraints.

[0137] In some implementations, the system can be deployed via software and cloud-based infrastructure. It can operate as a standalone application, a distributed service, or a Software-as-a-Service (SaaS) platform running in a virtualized computing environment. Cloud resources provide elastic computing, storage, and networking capabilities to extend user data processing, behavioral analytics, content creation, and automated workflow execution. Software components can be structured as microservices interconnected via application programming interfaces (APIs), enabling interoperability with third-party platforms, enterprise applications, and AI services. Containerization and orchestration frameworks support portability and resilience, while distributed databases or blockchain-based ledgers ensure transparency, data integrity, and immutability.

[0138] In other implementations, a hybrid approach combining local hardware resources with cloud-based infrastructure can be adopted. Latency-sensitive tasks (such as data reception, preprocessing, or real-time execution) can be performed locally on CPUs, DSPs, ASICs, FPGAs, or PLDs. Computationally intensive or large-scale functions (such as training machine learning models, market validation, or ledger management) can be performed in the cloud. In some configurations, the system can operate in synchronous mode, with local devices performing immediate control and feedback, while cloud services provide long-term analytics, scalability, and integration with external APIs. This hybrid deployment balances performance, power, cost, and scalability, enabling the system to flexibly adapt to different application environments.

[0139] In the specific implementation of the system for collecting user information described in this specification, provisions for protecting user privacy and data can be established. Specifically, users can be given the opportunity to opt in or out of procedures or features for collecting personal information (such as data related to user preferences or smart device usage patterns). Furthermore, in some implementations, data protection measures can be implemented to anonymize the collected information before it is stored or used. For example, a user's identity can be anonymized to prevent personally identifiable information from being linked to the identification or association of a specific user. Additionally, user preferences and interaction data can be generalized, potentially based on broader demographic categories rather than being linked to a single user.

[0140] The aspects described in this specification can be implemented using both hardware and software instructions. These instructions can be stored on various types of computer-readable media, including but not limited to random access memory (RAM), flash memory, read-only memory (ROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), registers, hard disks, removable disks, CD-ROMs, or any other form of storage media known in the art. In a typical configuration, the storage medium is connected to the processor, enabling the processor to read information from and write information to the medium. In some configurations, the storage medium may be integrated into the processor itself.

[0141] Additional notes

[0142] The terminology used in this description is intended to explain a particular implementation and should not be considered limiting. Unless the context clearly indicates otherwise, the singular forms “a” and “the” include the plural forms. The term “and / or” covers any combination of the listed items. Terms such as “includes” or “comprises” indicate the presence of the stated features but do not exclude additional features or components.

[0143] Various modifications will be apparent to those skilled in the art, and the principles herein can be applied to alternative embodiments without departing from the scope of this disclosure. The claims are intended to cover the widest scope consistent with the disclosed principles and features.

[0144] Implementations may include explicitly disclosed features as well as optional features that are not described in detail. Conversely, some implementations may omit features that are not explicitly disclosed. Such omissions do not narrow the scope of the claimed subject matter, as long as the disclosed features are present.

[0145] Features described individually may also be combined into a single embodiment. Conversely, features described in a single embodiment may be divided into individual embodiments or sub-combinations. Even where combination is initially required, one or more features may be removed or rearranged without departing from the invention.

[0146] In the accompanying drawings, the description of the process sequence should not be considered a strict requirement. Operations may occur in different orders or concurrently, and additional operations not illustrated may be inserted. Similarly, the schematic diagrams and drawings are illustrative, not drawn to scale, and are not intended as precise technical drawings. They are helpful for understanding but do not limit the invention to the described arrangements.

[0147] In some cases, multitasking and parallel processing may be advantageous. Depending on the specific implementation requirements, the described components may be shown as separate, but they may also be integrated. Software components may be packaged together or distributed throughout the system, depending on the circumstances. Other embodiments besides those described are also within the scope of the claims. The order of actions in the claims may be varied while still achieving the desired result. This flexibility in implementation is part of the invention.

[0148] While the invention has been described in conjunction with certain embodiments, those skilled in the art will understand that various modifications and adjustments can be made without departing from the scope of the invention. The specific embodiments presented are intended to illustrate the invention and not to limit its application or structure. Those skilled in the art will readily observe that various modifications and changes can be made to the apparatus and method while maintaining the teachings of the invention. Therefore, the foregoing disclosure should be construed as being limited only by the boundaries and limits of the appended claims.

Claims

1. A computer-implemented method for automated processing and execution, the computer- implemented method comprising: receiving data of a user including a desire of the user; analyzing the data of the user with one or more algorithms to identify at least one actionable solution corresponding to the desire of the user; generating structured digital content based on the analyzed data; and outputting the structured digital content in a format configured for presentation on a user device.

2. The method of claim 1, wherein the data of the user includes preferences, behavioral patterns, and market information.

3. The method of claim 1, wherein the desire of the user further includes a defined goal and associated categorical information.

4. The method of claim 1, wherein: the structured digital content includes an execution plan, impact analysis, marketing analysis, and / or design templates; and the generating includes proposing an execution plan and initiating execution of the plan through one or more execution agents and systems, application programming interfaces (APIs), or artificial intelligence processes included by the one or more execution agents.

5. The method of claim 4, wherein the structured digital content further includes feedback reports generated from community responses or expert reviews.

6. The method of claim 1, further comprising storing the structured digital content in a blockchain ledger.

7. The method of claim 1, further comprising validating the actionable solution through community voting or expert review prior to dissemination.

8. The method of claim 1, further comprising formatting the structured digital content for dissemination through channels including public networks, private groups, and / or enterprise platforms.

9. The method of claim 1, further comprising: analyzing user interaction and market response data associated with the structured digital content to generate success metrics; and analyzing public online content including social media posts, images, and / or profile data to determine user ideas, behaviors, and interests.

10. The method of claim 9, wherein the success metrics include engagement metrics, market fit indicators, and behavioral patterns.

11. The method of claim 1, wherein the method further comprises applying machine learning models to associate the desire of the user with digital resources, collaborators, and / or market opportunities.

12. The method of claim 1, further comprising associating the desire of the user with market platforms for executing the desire of the user, the market platforms including community voting, expert review, competitive ranking, crowdfunding, and / or revenue sharing.

13. The method of claim 1, further comprising tracking user growth by logging data, behavioral assessments, health information, and / or learning progress, and generating personalized insights or rewards accordingly. ​ ​ 14. A computer-implemented system for automated processing and execution, the computer- implemented system comprising: a memory storing instructions; and a processor coupled to the memory and configured to, when executing the instructions: receive data of a user including a desire of the user; analyze the data of a user with one or more algorithms to identify at least one actionable solution corresponding to the desire of the user; generate structured digital content based on the analyzed data; and output the structured digital content in a format configured for presentation on a user device.

15. The system of claim 14, wherein the data of a user includes preferences, behavioral patterns, and market information.

16. The system of claim 14, wherein the desire of the user includes a defined goal and associated categorical information.

17. The system of claim 14, wherein: the structured digital content includes an execution plan, impact analysis, marketing analysis, and / or design templates; the processor is further configured to propose an execution plan and initiate execution of the plan through one or more execution agents including a company, an application programming interface (API), and / or artificial intelligence.

18. The system of claim 14, wherein the processor is further configured to format the structured digital content for dissemination through channels including public networks, private groups, and / or enterprise platforms.

19. The system of claim 14, wherein the processor is further configured to: analyze user interaction and market response data associated with the structured digital content to generate success metrics including engagement metrics, market fit indicators, and behavioral patterns; and analyze content to determine ideas, behaviors, and interests of the user, wherein public online content includes social media posts, images, or profile data.

20. The system of claim 14, wherein the processor is further configured to associate the desire of the user with a market platform for execution of the desire of the user, and the market platform includes community voting, expert review, competitive ranking, crowdfunding, and / or revenue sharing. ​

Images