Dynamic hierarchical data system for ai-driven IP asset management

Abstract

A dynamic hierarchical data system for AI-driven IP asset management organizes digital assets into a hierarchical structure while retaining contextual and layered details, thereby enabling efficient queries and improved output quality. Embodiments of the invention dynamically adapt to AI workflows, ensuring scalability, interoperability, and comprehensive data management. Key features include a specialized metadata schema, AI interaction repository, multi-layer indexing, dynamic licensing, automation tools for metadata validation, and robust security and access control.

Description

(PATENT)DYNAMIC HIERARCHICAL DATA SYSTEM FOR AI-DRIVEN IP ASSET MANAGEMENTCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application is a continuation of U.S. Non-Provisional Patent Application No. 19 / 406,485, filed December 2, 2025, entitled “DYNAMIC HIERARCHICAL DATA SYSTEM FOR AI-DRIVEN IP ASSET MANAGEMENT”, and claims benefit of priority of U.S. Provisional Patent Application No. 63 / 727,512, filed December 3, 2024, entitled “DYNAMIC HIERARCHICAL DATA SYSTEM FOR AI-DRIVEN IP ASSET MANAGEMENT”, each of which are incorporated herein by reference in their entirety.TECHNICAL FIELD

[0002] Embodiments of the invention relate to a dynamic hierarchical data system for Al-driven IP asset management.BACKGROUND

[0003] Generative Al systems increasingly rely on vast, diverse datasets of digital assets — music, video, text, and 3D models. Conventional asset management systems typically organize these assets in flat, linear structures, focusing on final products rather than their constituent components. This approach leads to inefficiencies in query performance, metadata tagging, and scalability. For example, assembling an Al training dataset often requires repeated parsing across disjointed metadata fields, slowing workflows and increasing computational costs. Flat structures are also static, failing to adapt to dynamic, context-aware relationships between assets and metadata required by evolving Al workflows. As Al systems advance, there is an urgent need for hierarchical, scalable, and interoperable asset management solutions.SUMMARY

[0004] Embodiments of the invention provide a dynamic hierarchical data system for Al-driven IP asset management that organizes digital assets into a hierarchical structure while retaining contextual and layered details, thereby enabling efficient queries1184623667.1(PATENT) and improved output quality. Embodiments of the invention dynamically adapt to Al workflows, ensuring scalability, interoperability, and comprehensive data management. Key features include a specialized metadata schema, Al interaction repository, multilayer indexing, dynamic licensing, automation tools for metadata validation, and robust security and access control.

[0005] Embodiments of the invention introduce a hierarchical data structure, supported by a specialized metadata schema and an Al interaction repository, to solve these challenges. By organizing assets into logical layers — assets, stacks, and groups — the system enhances efficiency, reduces redundancy, and dynamically adapts to evolving Al requirements.BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Detailed descriptions of implementations of the present invention will be described and explained through the use of the accompanying drawings.

[0007] Figure 1 is a block diagram of a system architecture according to an embodiment of the invention;

[0008] Figure 2 shows a hierarchical data structure according to an embodiment of the invention;

[0009] Figures 3A and 3B show a specialized metadata schema according to an embodiment of the invention;

[0010] Figure 4 is a block diagram showing an Al interaction repository according to an embodiment of the invention;

[0011] Figure 5 is a block diagram showing a multi-layer indexing system according to the invention;

[0012] Figures 6A-6C show a schema for the hierarchical data structure according to qn embodiment of the invention;

[0013] Figures 7A-7C show asset contextualization examples according to an embodiment of the invention; and

[0014] Figure 8 is a block diagram that illustrates an example of a computer system in which at least some operations described herein can be implemented.2184623667.1(PATENT)

[0015] The technologies described herein will become more apparent to those skilled in the art from studying the Detailed Description in conjunction with the drawings. Embodiments or implementations describing aspects of the invention are illustrated by way of example, and the same references can indicate similar elements. While the drawings depict various implementations for the purpose of illustration, those skilled in the art will recognize that alternative implementations can be employed without departing from the principles of the present technologies. Accordingly, while specific implementations are shown in the drawings, the technology is amenable to various modifications.DETAILED DESCRIPTION

[0016] Generative Al systems rely on vast datasets of digital assets, including music, video, text, and 3D models. However, traditional asset management systems organize these assets in flat, linear structures that focus on final products rather than their components. This creates inefficiencies in query performance, metadata tagging, and scalability. For example, retrieving assets for an Al training dataset may require repeated parsing across disjointed metadata fields, slowing workflows and increasing computational costs. Flat structures are also limited by their static nature, failing to adapt to Al workflows that demand dynamic, context-aware relationships between assets and metadata. As Al systems evolve, hierarchical, scalable, and interoperable asset management solutions are urgently needed.

[0017] Embodiments of the invention introduce a hierarchical data structure, supported by a specialized metadata schema and an Al interaction repository, to solve these challenges. By organizing assets into logical layers— assets, stacks, and groups— the system enhances efficiency, reduces redundancy, and dynamically adapts to evolving Al requirements. The invention claimed herein solves this problem.

[0018] Embodiments of the invention address the inefficiencies of traditional flat data structures in asset management by introducing a dynamic, hierarchical framework tailored for Al systems. It organizes assets into logical levels — assets, stacks, and groups— paired with a specialized metadata schema and an Al interaction repository. This structure streamlines asset retrieval, reduces redundancy, and adapts to evolving Al workflows, improving scalability and interoperability. By enabling efficient querying and3184623667.1(PATENT) dynamic licensing mechanisms, the system significantly enhances the integration and management of intellectual property assets in Al environments.

[0019] State of the art systems do not work well because assets are typically provided in their final product form, without the context or layered details that contributed to their creation. This results in incomplete data that diminishes clarity and reduces the effectiveness of Al workflows. Embodiments of the invention improve on existing systems by organizing assets into a hierarchical structure that retains contextual and layered details, enabling more efficient queries and better-quality outputs. It dynamically adapts to Al workflows, ensuring scalability, interoperability, and comprehensive data management.

[0020] Also, it can produce several useful items by applying its core functionality in practical ways:Digital Asset Management Platform

[0021] Embodiments of the invention are implemented as a software platform that organizes, manages, and licenses digital assets for industries such as Al, media, and entertainment. This platform enable users to upload, tag, query, and license assets efficiently.Metadata-Driven Al Training Datasets

[0022] By applying the hierarchical organization and tagging features, embodiments of the invention generate highly structured and annotated datasets optimized for Al training, which are valuable for developers and researchers.Licensing and Royalty Management Tools

[0023] Embodiments of the invention enforce usage-based licensing, calculate royalties, and automate compliance workflows, creating a product tailored for industries reliant on intellectual property.Custom Content Portfolios

[0024] The hierarchical structure can generate curated content bundles, such as themed media libraries or project-specific asset collections, for clients in marketing, education, or entertainment.4184623667.1(PATENT)Interoperable Asset Repositories

[0025] By leveraging the interaction repository, Embodiments of the invention produce centralized repositories for managing assets used across multiple platforms, ensuring seamless integration and traceability.Scalable Cloud Asset Solutions

[0026] The scalable architecture allows for the creation of cloud-based asset management solutions tailored for high-demand environments, such as gaming, loT, or scientific research.Data-Driven Analytics Reports

[0027] Using the interaction logging and metadata validation tools, the invention can produce insights and reports on asset usage, licensing patterns, and workflow efficiency, offering value for decision-making. This invention is capable of generating a wide range of products and systems tailored to solve specific problems in digital asset management, licensing, and Al integration.System Architecture

[0028] Figure 1 is a block diagram of a system architecture according to an embodiment of the invention, which comprises;

[0029] 1. A centralized Al interaction repository (100) that logs and manages relationships between assets and Al systems. This repository dynamically maps asset usage and tracks interactions, enabling seamless integration with Al platforms. It also facilitates the monitoring of asset utilization for licensing purposes and enhances interoperability across platforms.

[0030] 2. Automation tools for metadata (1 10) comprising validation automation tools are used to maintain metadata quality across the system. These tools use Al to generate tags automatically based on asset characteristics and flag duplicate, incomplete, or inconsistent metadata for review. This minimizes manual intervention while ensuring data integrity.

[0031] 3. Dynamic licensing mechanism (120) which, in embodiments of the invention incorporate a dynamic licensing mechanism that supports usage-based workflows. When an asset is accessed, predefined licensing thresholds trigger automatic5184623667.1(PATENT) adjustments, with the option to integrate smart contracts for compliance and payment automation. This ensures fair compensation for asset usage and facilitates real-time licensing updates.

[0032] 4. Hierarchical data structure (130) which, in embodiments of the invention include a hierarchical framework for organizing digital assets, consisting of three levels. Individual assets, such as audio files, videos, or text documents, represent the smallest unit. Stacks are collections of related assets with defined parent-child relationships, such as a video file paired with its audio stems. Groups serve as high-level contextual collections that organize stacks and assets based on themes, projects, or purposes, such as a music album or film production.

[0033] 5. Multi-layer indexing system (140) which optimizes data retrieval. The system employs a multi-layer indexing framework. A primary index tracks all groups and their relationships, while a stack index maps parent-child relationships within stacks. Additionally, a direct asset index allows for rapid access to individual assets, ensuring efficient querying and minimal computational overhead.

[0034] 6. Physical and software components (150) which, in embodiments of the invention rely on a combination of physical and software elements. A robust database infrastructure supports the hierarchical data structure and indexing framework. The software platform handles metadata tagging, interaction logging, and licensing workflows, while a user interface provides tools for accessing and managing the system.

[0035] 7. Real-time metadata and asset updates (160) which maintain consistency.Embodiments of the invention include tools for real-time updates to metadata, stacks, and group relationships. Changes are dynamically propagated across the hierarchy, ensuring that all elements remain synchronized without disrupting workflows.

[0036] 8. Scalable architecture (170) which, in embodiments of the invention are designed for scalability, employing tiered storage to prioritize frequently accessed assets for faster retrieval. Embodiments of the invention are compatible with emerging database technologies, including vector databases and tensor indexing, ensuring adaptability to future advancements in asset management and Al integration.

[0037] 9. Security and access control (180) which, in embodiments of the invention incorporate robust security measures, including hashed identifiers to provide secure and6184623667.1(PATENT) unique referencing for assets, stacks, and groups. Role-based permissions control user access, ensuring that only authorized individuals can interact with specific assets or metadata.

[0038] 10. Specialized metadata schema (190). Dynamic metadata schema underpins the hierarchical structure, assigning descriptive and contextual tags to each asset, stack, and group. Descriptive tags capture asset-specific details such as instrument type or genre, while hierarchical tags define relationships between assets, stacks, and groups. Metadata dynamically adjusts in real time based on asset usage, ensuring accuracy and relevance.Implementation

[0039] The components of the invention are designed to work together seamlessly, creating a unified and scalable system.

[0040] Figure 2 shows a hierarchical data structure according to an embodiment of the invention. The hierarchical data structure serves as the foundation, organizing assets into interconnected levels of assets, stacks, and groups. In Figure 2 a group 200 includes any of stacks 210a, 210b and assts 220a, 220b, 220c, 220d, 220e. Stacks 210a, 210b also include respective assets 240a-240c and 230a-230d.

[0041] Figures 3A and 3B show a specialized metadata schema according to an embodiment of the invention. In Figure 3A a hierarchical data structure comprises a group 300, in this example, includes stacks 310a, 310b which, in turn, included respective assets 320a-320c and 325a-325e. The specialized metadata schema links these levels with dynamic, descriptive tags 330, enhancing discoverability and ensuring consistency. In the example shown in Figure 3B, the dynamic, descriptive tags comprise a UIIID, tag_name, and tag_category. Those skilled in the art will appreciate that other tags may be provided as desired.

[0042] Figure 4 is a block diagram showing an Al interaction repository according to an embodiment of the invention. In Figure 4, the Al interaction repository 420 logs relationships and usage between assets and Al systems. For example, a group 400 for Film Project A (400a) includes stacks 405 for Audio 1 (405a) and Video 1 (405b), each7184623667.1(PATENT) of which includes respective assets vocal.wav (410a) and sound_effect.wav (410c) and image.jpg (410c) and video. mp4 (41 Od).

[0043] The Al interaction repository provides a dynamic mapping 420a of the Group Film Project A (400a), usage tracking 420b that logs usage of the stacks 405a, 405b, and interoperability 420c. The dynamic mapping provides relevant data to the Al system 430, which in this example is OpenAL Those skilled in the art will appreciate that other Al systems may be used to practice the invention. The interoperability function interacts with a service 440, such a Gemini. Those skilled in the art will appreciate that other such services may be used to practice the invention.

[0044] Figure 5 is a block diagram showing a multi-layer indexing system according to the invention. The multi-layer indexing system ensures efficient data retrieval from the repository by mapping these relationships across the hierarchy. In Figure 5, a hierarchy includes a group index 500 which, in this example, includes the groups Film Project A (550) and Music Album B (560). Each group establishes a hierarchy and includes a stack index 510 for respective stacks, e.g. Audio 1 (405a) and Video 1 (405b) for the group Film Project A. Likewise, there is a direct asset index 520 for respective assets, e.g. vocal.wav 410a and sound_effect.wav 410b for stack Audio 1 and image.jpg 410c and video. mp4 41 Od for stack Video 1 .

[0045] In the example of Figure 5 a prompt 530 is entered, i.e. Find a sound effect from Film Project A that would fit well for this scene. The system provides as a response 540 sound_effect.wav 410b.

[0046] As discussed above in connection with Figure 1 embodiments of the invention a dynamic licensing mechanism integrates with the repository to adjust licensing workflows based on real-time usage. Automation tools for metadata validation maintain data integrity by generating and verifying metadata, ensuring that the hierarchy remains accurate. The physical and software components, including a database and user interface, support these processes and provide access to system tools. The scalable architecture ensures the system can handle large datasets, while real-time metadata and asset updates synchronize changes across all levels. Finally, security and access control safeguards relationships and access through hashed identifiers and permissions, ensuring the system’s reliability and security. Together, these components create an efficient and adaptable solution for managing digital assets in Al workflows.8184623667.1(PATENT)

[0047] Further to the discussion of Figure 1 above, the components of the invention work individually and together to create an innovative, scalable system for managing digital assets tailored to Al workflows. The hierarchical data structure provides a multitiered framework by organizing assets into individual files (assets), related collections (stacks), and contextual groups. This structure allows the system to streamline data relationships, enhancing both retrieval and scalability.

[0048] The specialized metadata schema dynamically generates descriptive and hierarchical tags for assets, stacks, and groups, ensuring accurate, context-aware organization and adaptability to real-time changes in usage or project requirements.

[0049] The Al interaction repository (see Figure 4) records how assets are accessed and used by Al platforms, mapping these interactions dynamically and facilitating interoperability across systems.

[0050] The multi-layer indexing system (see Figure 5) optimizes asset retrieval by using a layered approach: a primary index for groups, a stack index for parent-child relationships, and a direct asset index for individual files. This enables efficient queries, whether for individual assets or broad project groups.

[0051] The dynamic licensing mechanism automates compliance and calculates usage-based fees, integrating smart contracts to adjust licensing terms in real time as assets are used.

[0052] The automation tools for metadata validation leverages Al to ensure data accuracy by generating new metadata tags and flagging errors or inconsistencies for review, minimizing manual intervention.

[0053] The physical and software components provide the infrastructure necessary to support the system, including a database, indexing tools, and a user interface that allows for efficient management and querying of assets.

[0054] The scalable architecture ensures the system remains performant even with large datasets, prioritizing frequently accessed assets through tiered storage and supporting emerging technologies like vector databases.

[0055] Real-time metadata and asset updates ensure changes to assets, stacks, or groups are automatically propagated throughout the system, maintaining consistency and accuracy across all components.9184623667.1(PATENT)

[0056] Finally, security and access control protects the system by employing hashed identifiers for secure referencing and role-based permissions to regulate user access.

[0057] Together, these components create a robust, future-ready platform that solves inefficiencies in traditional asset management systems. By integrating hierarchical organization, dynamic metadata, efficient indexing, real-time updates, and advanced licensing mechanisms, embodiments of the invention optimize asset usage for Al workflows, ensuring scalability, interoperability, and secure compliance. This combination of features establishes a novel solution for managing intellectual property assets in evolving Al-driven environments.Logic

[0058] 1 . Hierarchical Relationship Logic

[0059] * If an asset is uploaded, then assign it to the lowest level (asset) in the hierarchy.

[0060] * If related assets are identified, then group them into a stack with parentchild relationships.

[0061] * If multiple stacks share a common purpose, then group them into a higher- level group.

[0062] 2. Metadata Schema Logic

[0063] * If an asset is added, then generate dynamic metadata tags based on type, content, and purpose.

[0064] * If asset usage or relationships change, then update metadata in real-time.

[0065] 3. Al Interaction Repository Logic

[0066] * If an Al system queries the repository, then map the request to relevant assets, stacks, or groups using metadata and indices.

[0067] * If predefined usage thresholds are met, then trigger licensing workflows and log interactions.

[0068] 4. Multi-Layer Indexing Logic

[0069] * If an asset is queried, then retrieve its location from the direct asset index.10184623667.1(PATENT)

[0070] * If a stack or group is queried, then retrieve all associated child assets using the primary and stack indices.

[0071] 5. Dynamic Licensing Logic

[0072] * If an asset or stack is used, then check metadata for usage thresholds and licensing terms.

[0073] * If thresholds are triggered, then calculate fees and initiate a smart contract workflow.

[0074] 6. Automation and Validation Logic

[0075] * If metadata is incomplete or inconsistent, then flag it for review and recommend corrections.

[0076] * If a new asset is added, then automatically generate and validate metadata.

[0077] 7. Real-Time Update Logic

[0078] * If changes occur in an asset, stack, or group, then propagate updates across the hierarchy and synchronize with indices.

[0079] 8. Security and Access Control Logic

[0080] * If a user requests access, then verify permissions and grant access if authorized, logging the interaction.System Design

[0081] Figures 6A-6C show a schema for the hierarchical data structure according to an embodiment of the invention.

[0082] In Figure 6A a repository 600 contains groups 610 that contain related stacks 620 that, in turn contain related assets 520a. Group 610 also contains assets 610a.

[0083] Figure 6B shows group 650 that contains two stacks 630, 640 as well as an asset 650a. Stacks 630, 640 in turn contain respective assets 630a, 640a.

[0084] Figure 6C shows assets 670 that are contained within the repository. Also shown is a stack 660 that contains assets 660a.1 1184623667.1(PATENT)

[0085] In embodiments of the invention the database design has three levels: assets (files), stacks (grouped assets), and groups (collections of stacks). Unique identifiers and metadata are used to link and query efficiently - see Figures 3A and 3B.

[0086] Those skilled in the art will appreciate that the database is not limited to a single hierarchy structure, (Universes -> Group -> Stacks -> Assets). The system is designed to adapt to different industries with different hierarchical needs. Some examples are shown in Table 1 below.Table 1: Hierarchy Examples

[0087] Each domain would have its own specialized metadata (HIPAA flags, privilege designations, building codes, etc.) that inherit through the hierarchy.

[0088] Specialized metadata schema are implemented by developing a tagging system for assets, stacks, and groups, using Al to generate metadata dynamically and updating in real time as relationships change.

[0089] The Al interaction repository is created as a repository to log and map asset interactions with Al systems, dynamically linking them through metadata. API integrations are added for seamless platform interoperability.

[0090] The multi-layer indexing system is built as an indexing system for groups, stacks, and assets to enable fast data retrieval and ensure updates sync in real time.

[0091] The dynamic licensing mechanism is developed as a system to monitor usage, calculate licensing fees, and enforce compliance via smart contracts, integrated with metadata and the repository.12184623667.1(PATENT)

[0092] The automation tools for metadata validation use Al to generate, validate, and correct metadata while automating error detection to maintain accuracy with minimal manual input.

[0093] The physical and software components set up a database and interface for managing uploads, metadata, and queries, integrated with backend services for smooth operations. Implementing

[0094] The scalable architecture is a scalable system using tiered storage for frequent access and cloud solutions for large datasets, supporting emerging technologies.

[0095] Real-time metadata and asset updates are programmed by creating a system to sync updates across assets, stacks, and groups instantly using event-driven architecture for consistency.

[0096] Security and access control is incorporated by using hashed identifiers and role-based permissions to secure access and encryption to protect data integrity.

[0097] Necessary elements in embodiments of the invention include the:• Hierarchical data structure which is essential for organizing assets into assets, stacks, and groups, enabling efficient querying and management;• Specialized metadata schema which is critical for tagging and defining relationships between assets, ensuring organization and discoverability;• Al interaction repository which is vital for logging interactions, enabling interoperability with Al systems, and supporting licensing workflows;• Multi-layer indexing system which is necessary for fast and accurate data retrieval across the hierarchy;• Dynamic licensing mechanism which is key for enforcing usage tracking and monetization through licensing compliance; and• Physical and software components which are essential for database infrastructure and a user interface to manage assets and metadata.

[0098] Optional elements in embodiments of the invention include the:• Automation tools for metadata validation which are useful for maintaining accuracy but not essential for small-scale implementations;13184623667.1(PATENT)• Scalable architecture which is optional for smaller datasets where scalability is not required;• Real-time metadata and asset updates which improve efficiency but can be replaced with manual or batch updates in less dynamic systems; and• Security and access control which is critical for sensitive data but optional in low- risk or internal-only systems.

[0099] In additional embodiments of the invention enhancements can include:• Advanced analytics tools which provide insights into usage trends and optimization opportunities;• Machine learning integration which automates metadata tagging and licensing suggestions for improved efficiency;• Blockchain for licensing which enhances transparency and trust for multi-party collaborations; and• Audit and reporting features which strengthen compliance tracking and add user value through detailed reports.• Hierarchical Data Structure (Item 1 ) Additional layers, such as sub-stacks or subgroups, can be added, or a flat structure with embedded metadata relationships can simulate the same organizational hierarchy.

[0100] Further, enhancements of the basic elements of the invention can include:• Specialized metadata schema: Metadata could be managed in a separate database or integrated into external systems, dynamically referenced during queries to maintain flexibility;• Al interaction repository: The repository could be replaced with a decentralized ledger such as blockchain, maintaining interaction logs and mapping functions for assets and Al systems;• Multi-layer indexing system : Indexing could be consolidated into a single relational model, or graph databases could represent relationships as nodes and edges while preserving retrieval efficiency;• Dynamic licensing mechanism: Licensing could operate without smart contracts by using a rule-based engine or integrating terms directly into the metadata14184623667.1(PATENT) schema for dynamic enforcement;• Automation tools for metadata validation: Validation could be outsourced to third- party systems via APIs or handled manually for smaller datasets;• Physical and software components: The system could be distributed across multiple servers managing separate functions, maintaining performance while decentralizing operations;• Scalable architecture: Scalability can be achieved through horizontal database sharding or omitted entirely for smaller datasets while retaining functionality;• Real-time metadata and asset updates: Updates could occur in scheduled batches or via polling systems instead of real-time synchronization, ensuring consistency more gradually; and• Security and access control: Role-based permissions can be replaced by API access keys or token-based systems, while hashed identifiers could be substituted with encryption.Operation

[0101] Asset Upload and Organization: The user uploads assets, e.g. audio files, videos, text documents, into the system. The assets are automatically organized into the hierarchical structure of assets, stacks, and groups, based on their relationships and purpose. For example, a video file may be grouped with its audio stems and visual effects layers into a stack, which is then placed into a project-level group.

[0102] Metadata Tagging: As assets are uploaded, the system assigns descriptive and contextual metadata using Al algorithms. For instance, an audio file could be tagged with attributes such as “instrument: guitar” and “genre: rock.” The system generates metadata tags, and users can add their own tags for further refinement, with user tags and system tags stored in separate fields.

[0103] Querying and Retrieval: Users or Al platforms query the system to retrieve specific assets, stacks, or groups. For example, an Al model could request only the vocal stem from a music project. The indexing system ensures efficient retrieval by directing the query to the relevant hierarchical level without scanning unrelated data.15184623667.1(PATENT)

[0104] Interaction Logging: The system logs all interactions between Al platforms and assets in the Al Interaction Repository. For instance, when an Al model uses an image for training, the repository records the interaction, enabling traceability and usage tracking.

[0105] Dynamic Licensing Enforcement: The licensing mechanism monitors how assets are used. If an Al platform exceeds predefined usage thresholds, such as training on more than 10% of a dataset, the system calculates the appropriate licensing fee and triggers compliance workflows, including smart contract execution for payment.

[0106] Real-Time Updates and Management: As new assets are added, relationships are modified, or metadata is updated, the system propagates changes dynamically across the hierarchy. This ensures all users and Al systems interact with the most accurate and up-to-date information.

[0107] Validation and Error Correction: The system uses automation tools to validate metadata, flagging errors or inconsistencies for correction. This ensures that all assets remain properly described and organized, preventing issues during queries or licensing.

[0108] Scalability for Large Datasets: For larger projects, the system’s scalable architecture prioritizes frequently accessed assets for faster retrieval and handles growing datasets seamlessly. Cloud-based infrastructure ensures smooth operation even under high demand.

[0109] User Access and Security: Users interact with the system through a secure user interface, where role-based permissions regulate access. For example, a team member might be allowed to view and tag assets but not initiate licensing workflows.

[0110] Integration with Al Platforms: The system provides APIs that allow Al platforms to query, retrieve, and interact with assets directly, ensuring interoperability. For instance, an Al model could access specific training data with predefined licensing terms automatically enforced by the system.

[0111] Embodiments of the invention can also be applied across various fields and technologies beyond Al workflows. Its core components — hierarchical data organization,16184623667.1(PATENT) dynamic metadata, interaction logging, and licensing enforcement — are versatile and adaptable for other uses, including:

[0112] Healthcare Data Management: Organizing patient records, medical imaging, and lab results into hierarchical groups and tagging them with metadata can improve access, traceability, and regulatory compliance-commerce and

[0113] Inventory Systems: The system can organize product catalogs into hierarchical levels with metadata for features and pricing, while licensing mechanisms could manage product usage rules.

[0114] Education and Research: Academic institutions could use it to manage datasets, publications, and multimedia, improving discoverability with hierarchical organization and metadata tagging, while controlling usage for educational Al applications.

[0115] Gaming and Virtual Reality: The system could manage game assets like textures, models, and soundtracks, with licensing features tracking third-party asset usage in games or VR environments.

[0116] Content Distribution and Licensing: Media companies could streamline asset management for films, music, and digital art, using licensing workflows to enforce proper usage rights’ Device Management devices and their data could be organized into hierarchical groups for efficient querying, with licensing regulating access to devicegenerated data.

[0117] Scientific Simulations: Researchers could manage simulation models, raw data, and results using metadata and interaction logging to track collaborative usage. This invention’s efficiency, traceability, and licensing capabilities make it adaptable to a wide range of asset and data management challenges, particularly in technology-driven environments.

[0118] Embodiments of the invention can also be used produce several useful items by applying its core functionality in practical ways:

[0119] Digital Asset Management Platform: Embodiments of the invention can be implemented as a software platform that organizes, manages, and licenses digital assets for industries such as Al, media, and entertainment. This platform would enable users to upload, tag, query, and license assets efficiently.17184623667.1(PATENT)

[0120] Metadata-Driven Al Training Datasets: By applying the hierarchical organization and tagging features, the invention can generate highly structured and annotated datasets optimized for Al training, which are valuable for developers and researchers.

[0121] Licensing and Royalty Management Tools: The invention can produce a system to enforce usage-based licensing, calculate royalties, and automate compliance workflows, creating a product tailored for industries reliant on intellectual property.

[0122] Custom Content Portfolios: The hierarchical structure can generate curated content bundles, such as themed media libraries or project-specific asset collections, for clients in marketing, education, or entertainment.

[0123] Interoperable Asset Repositories: By leveraging the interaction repository, the invention can produce centralized repositories for managing assets used across multiple platforms, ensuring seamless integration and traceability.

[0124] Scalable Cloud Asset Solutions: The scalable architecture allows for the creation of cloud-based asset management solutions tailored for high-demand environments, such as gaming, loT, or scientific research.

[0125] Data-Driven Analytics Reports: Using the interaction logging and metadata validation tools, the invention can produce insights and reports on asset usage, licensing patterns, and workflow efficiency, offering value for decision-making. This invention is capable of generating a wide range of products and systems tailored to solve specific problems in digital asset management, licensing, and Al integration.Database Schema and Relationships

[0126] Embodiment of the invention use four primary entity tables and relationship tables to connect them:Primary Entities:• Asset -The smallest unit. Contains file information, metadata, Al / human input statement references, embeddings, content tags, and pricing terms.• Asset Stack -A collection of related assets. Contains name, description, type, and collaborator information.• Asset Group -A collection of assets and / or asset stacks. Contains name, description, and18184623667.1(PATENT) company / user attribution.• Asset Universe -The highest level container representing a property, artist, franchise, or brand. Contains name, description, and company / user attribution.Relationship Tables:• Asset : Asset Stack -Links assets to stacks. Includes a "role" field and a "chronological order" integer that allows assets within a stack to be arranged in linear temporal sequence for easy understanding and processing.• Asset Group : Asset or Asset Stack -Links either assets or asset stacks to a group. Notably, an asset group cannot contain an asset that already has a relationship to an asset stack within that same group. This avoids redundancy -an asset only appears in a group directly if it has no stack relationship within that group. The same logic applies at the universe level.• Universe - Universe-level relationships include: o Universe : Group o Universe : Stack o Universe : Asset• Temporal / Chronological Ordering — Nested Asset StacksEmbodiments of the invention support two types of asset stacks: o Temporal Stacks — organized by time segments (e.g., 0:00-0:15, 0:15-0:30), which can be as granular as milliseconds; and o Vertical Stacks — contain all assets (audio, video, etc.) that appear within a given temporal segment.

[0127] A temporal stack can contain relationships to multiple vertical stacks, where each vertical stack has an index correlating to its position on the timeline. This allows the system to organize something such as a film where one can query "everything happening at 1 :23:45" and get all relevant audio, video, and metadata for that moment.

[0128] This also applies to narrative / character development — for franchises with sequels and prequels, characters can be placed on a timeline based on when events occur in the story (not release order).19184623667.1(PATENT)Ownership Records:

[0129] A unified ownership table tracks ownership across all hierarchy levels. A single record can reference an asset, asset stack, or asset group, along with owning user / company, ownership percentage, status, and approval chain information.

[0130] True ownership is assigned at the individual asset level. If ownership is applied at a stack, group, or universe level, it inherits downward to all contained assets. Users / companies must then confirm the inherited ownership is correct (in case there are exceptions, such as a photographer who co-owns one specific image of a large set inside a group). This follows the same inheritance pattern as the access / omit permissions.Hierarchy Rules and Example

[0131] The hierarchy enforces non-redundancy: if an asset belongs to a stack, and that stack belongs to a group, the asset is not separately linked to the group. It is accessed through the stack. See table 2 below.Table 2: Example - Harry Poter

[0132] The asset stack arranges assets in a linear chain temporal format so the sequence is preserved and easy to process.Metadata Inheritance and Deduplication

[0133] The hierarchy functions like a binder: the universe is the binder, groups are chapters, stacks are pages, and assets are individual words.

[0134] When the same metadata appears at multiple levels, e.g. "2023" tagged at both the asset level and the group level, the system deduplicates - it only returns that value once. However, the system always tracks which level was actually queried and20184623667.1(PATENT) how the asset was reached: via direct asset query, through a stack, through a group, or through a universe.

[0135] When Al systems pull data at any level, if that asset has contextual relationships, the system can also reference information within those relationships. This allows Al outputs to be more refined and thorough by incorporating hierarchical context.Query and Indexing Logic

[0136] The system does not route queries to a single "correct" tier. Instead, it searches all tiers independently.

[0137] Assets are always searched as the base tier. Stacks, groups, and universes are additional context layers. If a query gets a hit at a higher level (stack, group, or universe), that triggers an additional search -either deeper within that container to find related assets / stacks, or zoomed out to find related parent containers.

[0138] This approach serves two purposes: it acts as a safety check ensuring nothing is missed, and it helps Al systems discover assets that might not have surfaced through a direct asset search alone.Access Control Logic

[0139] Each hierarchy level has its own access / omit Boolean. This is also true for any dynamically editable permission set over the usage and terms of an asset.

[0140] Access control works top-down with inheritance:• If a universe is set to "omit," all child elements (groups, stacks, assets) are omitted automatically.• If a single asset within a universe is set to "omit," only that asset is affected -sibling assets and parent containers remain accessible.

[0141] This allows broad restrictions at high levels while preserving granular control at lower levels.21184623667.1(PATENT)EMBODIMENTSContent Versioning and Lineage Tracker

[0142] This embodiment uses the hierarchical structure to track the full version history and derivative chain of assets. When content is modified, remixed, sampled, or otherwise transformed into new works, the system maintains parent-child relationships between the original and all derivatives, and can trace exactly which tier of the asset’s data was referenced. Metadata inheritance allows rights and restrictions from original assets to flow automatically to downstream derivatives. The Al interaction repository can log which specific versions of an asset were accessed, creating an auditable record of exactly what content an Al system used. This is particularly relevant for copyright disputes where the question is whether a model trained on an original work or a licensed derivative.Synthetic Data Integration Framework

[0143] This embodiment addresses the growing need to organize Al-generated content alongside human-created content while maintaining clear distinctions between them. The metadata schema includes flags indicating whether assets are human-created or Al-generated, and these flags propagate through the hierarchy via inheritance. When synthetic assets are derived from human-created source material, the system maintains links back to those sources. The Al interaction repository tracks when synthetic data is subsequently used to train other Al systems, creating a synthetic-to-synthetic lineage chain. This supports quality control, rights management for original creators whose work informed the synthetic outputs, and tracking to prevent issues with Al models training on other Al outputs.Al Training Marketplace Platform

[0144] This embodiment is a commercial platform where intellectual property owners can make their hierarchically organized assets available for licensed Al training. The hierarchical structure enables flexible licensing at any level — individual assets, complete stacks, groups, or entire universe containers — with different pricing at each tier. The system's distinction between training access and inference access allows for22184623667.1(PATENT) differentiated pricing based on how Al systems intend to use the content. The Al Interaction Repository provides the usage metering necessary for pay-per-use or consumption-based licensing models. This positions the system as infrastructure for an emerging market in licensed Al training data.Domain-Specific Implementations

[0145] This embodiment covers specialized applications of the hierarchical system tailored to specific industries. The core structure remains consistent, but the hierarchy tiers, metadata schemas, and access controls are adapted to industry requirements. Examples include medical imaging repositories where the hierarchy organizes patient studies and the metadata schema handles HIPAA compliance and de-identification requirements; legal document systems where privilege designations and confidentiality flags inherit through document hierarchies; and manufacturing / CAD libraries where the hierarchy organizes assemblies and components while metadata tracks certifications and export control restrictions. Each vertical implementation demonstrates the flexibility of the hierarchical approach while addressing domain-specific regulatory and operational needs.Real-Time Asset Assembly Engine

[0146] This embodiment uses the hierarchical structure to dynamically assemble assets from different levels of the hierarchy in real time for Al inference, personalization, or content generation. Rather than returning static, pre-defined collections, the system can compose responses to Al access requests by pulling assets from multiple stacks, groups, or containers based on query parameters. The multi-layer indexing system enables fast retrieval across hierarchy levels, and the Al Interaction Repository logs these dynamic assemblies. This supports use cases like personalized content delivery, realtime Al-assisted creation tools, and inference systems that need to reference multiple related assets simultaneously.23184623667.1(PATENT)Asset Contextualization Examples

[0147] Figures 7A-7C show asset contextualization examples according to an embodiment of the invention.

[0148] In Figure 7A an asset group: album 700 includes three tracks 710, i.e. Starlight Dreams, Midnight Walk, Echoes of You. In this example the asset stack: song 720 is for Echoes of You and the asset: stem I file 730 includes Synth Arps.

[0149] In Figure 7B an asset group: album 700 includes three tracks 710, i.e. Starlight Dreams, Midnight Walk, Echoes of You. In this example the asset stack: song 740 is for Midnight Walk and the asset: stem / file 750 includes Vocals, lead vocals with reverb.

[0150] In Figure 7C an asset group: album 700 includes three tracks 710, i.e. Starlight Dreams, Midnight Walk, Echoes of You. In this example the asset stack: song 760 is for Starlight Dreams and the asset: stem / file 770 includes Vocals, lead vocal with minimum processing.Computer System

[0151] Figure 8 is a block diagram that illustrates an example of a computer system 800 in which at least some operations described herein can be implemented. As shown, the computer system 800 can include: one or more processors 802, main memory 806, non-volatile memory 810, a network interface device 812, a video display device 818, an input / output device 820, a control device 822, e.g. keyboard and pointing device, a drive unit 824 that includes a machine-readable (storage) medium 826, and a signal generation device 830 that are communicatively connected to a bus 816. The bus 816 represents one or more physical buses and / or point-to-point connections that are connected by appropriate bridges, adapters, or controllers. Various common components, e.g. cache memory, are omitted from Figure 8 for brevity. Instead, the computer system 800 is intended to illustrate a hardware device on which components illustrated or described24184623667.1(PATENT) relative to the examples of the figures and any other components described in this specification can be implemented.

[0152] The computer system 800 can take any suitable physical form. For example, the computing system 800 can share a similar architecture as that of a server computer, personal computer (PC), tablet computer, mobile telephone, game console, music player, wearable electronic device, network-connected ("smart") device, e.g. a television or home assistant device, AR / VR systems, e.g. head-mounted display, or any electronic device capable of executing a set of instructions that specify actions to be taken by the computing system 800. In some implementations, the computer system 800 can be an embedded computer system, a system-on-chip (SOC), a single-board computer system (SBC), or a distributed system such as a mesh of computer systems, or it can include one or more cloud components in one or more networks. Where appropriate, one or more computer systems 800 can perform operations in real time, in near real time, or in batch mode.

[0153] The network interface device 812 enables the computing system 800 to mediate data in a network 814 with an entity that is external to the computing system 800 through any communication protocol supported by the computing system 800 and the external entity. Examples of the network interface device 812 include a network adapter card, a wireless network interface card, a router, an access point, a wireless router, a switch, a multilayer switch, a protocol converter, a gateway, a bridge, a bridge router, a hub, a digital media receiver, and / or a repeater, as well as all wireless elements noted herein.

[0154] The memory, e.g. main memory 806, non-volatile memory 810, machine- readable medium 826, can be local, remote, or distributed. Although shown as a single medium, the machine-readable medium 826 can include multiple media, e.g. a centralized / distributed database and / or associated caches and servers, that store one or more sets of instructions 828. The machine-readable medium 826 can include any medium that is capable of storing, encoding, or carrying a set of instructions for execution by the computing system 800. The machine-readable medium 826 can be non-transitory25184623667.1(PATENT) or comprise a non-transitory device. In this context, a non-transitory storage medium can include a device that is tangible, meaning that the device has a concrete physical form, although the device can change its physical state. Thus, for example, non-transitory refers to a device remaining tangible despite this change in state.

[0155] Although implementations have been described in the context of fully functioning computing devices, the various examples are capable of being distributed as a program product in a variety of forms. Examples of machine-readable storage media, machine-readable media, or computer-readable media include recordable-type media such as volatile and non-volatile memory 810, removable flash memory, hard disk drives, optical disks, and transmission-type media such as digital and analog communication links.

[0156] In general, the routines executed to implement examples herein can be implemented as part of an operating system or a specific application, component, program, object, module, or sequence of instructions (collectively referred to as "computer programs"). The computer programs typically comprise one or more instructions, e.g. instructions 804, 808, 828, set at various times in various memory and storage devices in computing devices. When read and executed by the processor 802, the instructions cause the computing system 800 to perform operations to execute elements involving the various aspects of the disclosure.REMARKS

[0157] The terms “example,” “embodiment,” and “implementation” are used interchangeably. For example, references to “one example” or “an example” in the disclosure can be, but not necessarily are, references to the same implementation; and such references mean at least one of the implementations. The appearances of the phrase “in one example” are not necessarily all referring to the same example, nor are separate or alternative examples mutually exclusive of other examples. A feature, structure, or characteristic described in connection with an example can be included in26184623667.1(PATENT) another example of the disclosure. Moreover, various features are described that can be exhibited by some examples and not by others. Similarly, various requirements are described that can be requirements for some examples but not for other examples.

[0158] The terminology used herein should be interpreted in its broadest reasonable manner, even though it is being used in conjunction with certain specific examples of the invention. The terms used in the disclosure generally have their ordinary meanings in the relevant technical art, within the context of the disclosure, and in the specific context where each term is used. A recital of alternative language or synonyms does not exclude the use of other synonyms. Special significance should not be placed upon whether or not a term is elaborated or discussed herein. The use of highlighting has no influence on the scope and meaning of a term. Further, it will be appreciated that the same thing can be said in more than one way.

[0159] Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense — that is to say, in the sense of “including, but not limited to.” As used herein, the terms “connected,” “coupled,” and any variants thereof mean any connection or coupling, either direct or indirect, between two or more elements; the coupling or connection between the elements can be physical, logical, or a combination thereof. Additionally, the words “herein,” “above,” “below,” and words of similar import can refer to this application as a whole and not to any particular portions of this application. Where context permits, words in the above Detailed Description using the singular or plural number may also include the plural or singular number, respectively. The word “or” in reference to a list of two or more items covers all of the following interpretations of the word: any of the items in the list, all of the items in the list, and any combination of the items in the list. The term “module” refers broadly to software components, firmware components, and / or hardware components.

[0160] While specific examples of technology are described above for illustrative purposes, various equivalent modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize. For example, while processes or blocks27184623667.1(PATENT) are presented in a given order, alternative implementations can perform routines having steps, or employ systems having blocks, in a different order, and some processes or blocks may be deleted, moved, added, subdivided, combined, and / or modified to provide alternative or sub-combinations. Each of these processes or blocks can be implemented in a variety of different ways. Also, while processes or blocks are at times shown as being performed in series, these processes or blocks can instead be performed or implemented in parallel, or can be performed at different times. Further, any specific numbers noted herein are only examples such that alternative implementations can employ differing values or ranges.

[0161] Details of the disclosed implementations can vary considerably in specific implementations while still being encompassed by the disclosed teachings. As noted above, particular terminology used when describing features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the invention with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the invention to the specific examples disclosed herein, unless the above Detailed Description explicitly defines such terms. Accordingly, the actual scope of the invention encompasses not only the disclosed examples but also all equivalent ways of practicing or implementing the invention under the claims. Some alternative implementations can include additional elements to those implementations described above or include fewer elements.

[0162] Any patents and applications and other references noted above, and any that may be listed in accompanying filing papers, are incorporated herein by reference in their entireties, except for any subject matter disclaimers or disavowals, and except to the extent that the incorporated material is inconsistent with the express disclosure herein, in which case the language in this disclosure controls. Aspects of the invention can be modified to employ the systems, functions, and concepts of the various references described above to provide yet further implementations of the invention.28184623667.1(PATENT)

[0163] To reduce the number of claims, certain implementations are presented below in certain claim forms, but the applicant contemplates various aspects of an invention in other forms. For example, aspects of a claim can be recited in a means-plus- function form or in other forms, such as being embodied in a computer-readable medium. A claim intended to be interpreted as a means-plus-function claim will use the words “means for.” However, the use of the term “for” in any other context is not intended to invoke a similar interpretation. The applicant reserves the right to pursue such additional claim forms either in this application or in a continuing application.29184623667.1

Claims

(PATENT)CLAIMS l / We claim:1 . A system for managing digital assets for generative artificial intelligence (Al) workflows, comprising: a hierarchical data structure configured to organize digital assets into at least three logical levels, including:(i) assets,(ii) stacks comprising collections of related assets with defined parent-child relationships, and(iii) groups comprising collections of stacks and / or assets organized by context, theme, or project; a specialized metadata schema configured to assign descriptive and contextual metadata tags to each asset, stack, and group, wherein said metadata schema supports dynamic, real-time updates and inheritance of metadata across hierarchy levels; an Al interaction repository configured to log, map, and manage relationships and usage interactions between assets and Al systems, including dynamic mapping of asset usage, interoperability with external Al platforms, and usage tracking for licensing purposes; and a multi-layer indexing system comprising:(i) a primary index for groups,(ii) a stack index for parent-child relationships within stacks, and(iii) a direct asset index for rapid access to individual assets2. The system of claim 1 , further comprising: a dynamic licensing mechanism configured to monitor asset usage, enforce usage-based licensing terms, calculate royalties, and automate compliance workflows, optionally integrating smart contracts for payment automation.

3. The system of claim 1 , further comprising: automation tools for metadata validation configured to generate, validate, and correct metadata using Al algorithms, and to flag duplicate, incomplete, or inconsistent metadata for review.30184623667.1(PATENT)4. The system of claim 1 , further comprising: physical and software components comprising a database infrastructure supporting the hierarchical data structure and indexing framework, a software platform for metadata tagging, interaction logging, and licensing workflows, and a user interface for accessing and managing the system.

5. The system of claim 1 , further comprising: real-time update tools configured to propagate changes to metadata, stacks, and group relationships dynamically across the hierarchy.

6. The system of claim 1 , further comprising: a scalable architecture employing tiered storage and supporting emerging database technologies for efficient retrieval and adaptability to large datasets.

7. The system of claim 1 , further comprising: security and access control mechanisms comprising hashed identifiers for secure referencing and role-based permissions for user access control.

8. The system of claim 1 , wherein the hierarchical data structure further comprises additional layers, including sub-stacks or sub-groups, to support more granular organization of assets.

9. The system of claim 1 , wherein the specialized metadata schema includes unique identifiers, tag names, tag categories, and supports deduplication and inheritance of metadata across hierarchy levels.

10. The system of claim 1 , wherein the Al interaction repository is further configured to log version history and derivative chains of assets, enabling traceability of content lineage and usage for copyright compliance.1 1 . The system of claim 1 , wherein the dynamic licensing mechanism is further configured to differentiate between training access and inference access for Al systems,31184623667.1(PATENT) enabling tiered licensing and royalty calculation.

12. The system of claim 1 , wherein the automation tools for metadata validation are further configured to use machine learning algorithms to suggest metadata tags and licensing terms based on asset characteristics and usage patterns.

13. The system of claim 1 , wherein the scalable architecture is implemented as a cloud-based solution supporting horizontal sharding and integration with vector databases and tensor indexing.

14. The system of claim 1 , wherein the security and access control mechanisms further comprise encryption of asset data and token-based authentication for API access.

15. A digital asset management platform for generative Al workflows, comprising the system of claim 1 , wherein the platform is configured to enable users to upload, tag, query, and license digital assets, and to generate structured Al training datasets, curated content portfolios, interoperable asset repositories, scalable cloud asset solutions, and data-driven analytics reports.

16. The system of claim 1 , wherein the hierarchical data structure, metadata schema, and access control mechanisms are adapted for domain-specific implementations, including healthcare data management, legal document management, manufacturing / CAD libraries, and gaming / virtual reality asset management.

17. The system of claim 1 , wherein the metadata schema includes flags indicating whether assets are human-created or Al-generated, and wherein the system maintains lineage links between synthetic assets and their human-created source material.

18. The system of claim 1 , wherein the Al interaction repository is configured to log and trace synthetic-to-synthetic lineage chains for Al-generated content.

19. An Al training marketplace platform, comprising the system of claim 1 , wherein intellectual property owners can make hierarchically organized assets available for32184623667.1(PATENT) licensed Al training, with flexible licensing and differentiated pricing at each hierarchy level.

20. The system of claim 1 , further comprising a real-time asset assembly engine configured to dynamically assemble assets from multiple hierarchy levels in response to Al access requests, enabling personalized content delivery and real-time Al-assisted creation.21 . The system of claim 1 , wherein access control is implemented with top-down inheritance, such that access restrictions at higher hierarchy levels propagate to all child elements, while granular control is preserved at lower levels.

22. The system of claim 1 , wherein the database schema comprises entity tables for assets, asset stacks, asset groups, and asset universes, and relationship tables linking assets to stacks, stacks to groups, and groups to universes, with non-redundancy enforced by hierarchical rules.

23. The system of claim 1 , further comprising: a content versioning and lineage tracker configured to maintain parent-child relationships between original and derivative assets, and to propagate rights and restrictions through metadata inheritance.

24. The system of claim 1 , further comprising analytics tools configured to generate reports on asset usage, licensing patterns, and workflow efficiency using data from the Al interaction repository and metadata validation tools.

25. A method for managing digital assets for generative Al workflows, comprising: uploading digital assets to a hierarchical data structure; automatically organizing the assets into assets, stacks, and groups based on relationships and context; generating and assigning dynamic metadata tags to each asset, stack, and group using Al algorithms; querying the hierarchical data structure to retrieve assets, stacks, or groups using33184623667.1(PATENT) the multi-layer indexing system; logging interactions between Al platforms and assets in the Al interaction repository; and monitoring asset usage and enforcing licensing terms using the dynamic licensing mechanism.

26. The method of claim 25, further comprising: propagating updates to metadata, stacks, and groups in real time across the hierarchy.

27. The method of claim 25, further comprising: validating and correcting metadata using automation tools.

28. The method of claim 25, further comprising: controlling user access to assets, stacks, and groups using role-based permissions and hashed identifiers.

29. A non-transitory, computer-readable storage medium comprising instructions recorded thereon, wherein the instructions, when executed by at least one data processor of a system, cause the system to: organize digital assets into a hierarchical structure comprising assets, stacks, and groups; assign dynamic, descriptive, and contextual metadata to each asset, stack, and group; log and manage relationships and interactions between assets and Al systems in an Al interaction repository; employ a multi-layer indexing system for efficient data retrieval across the hierarchy; implement a dynamic licensing mechanism that adjusts licensing terms based on asset usage and triggers compliance workflows; use automation tools for metadata validation and error correction; propagate real-time updates to metadata, stacks, and groups across the34184623667.1(PATENT) hierarchy; enforce security and access control using hashed identifiers and role-based permissions.

30. The storage medium of claim 29, wherein the multi-layer indexing system comprises any of: a primary index for groups; a stack index for parent-child relationships within stacks; and a direct asset index for individual assets.31 . A system comprising: at least one hardware processor; and at least one non-transitory memory storing instructions, which, when executed by the at least one hardware processor, cause the system to: upload digital assets to a hierarchical data structure; automatically organize the assets into assets, stacks, and groups based on relationships and context; generate and assign dynamic metadata tags to each asset, stack, and group using Al algorithms; query the hierarchical data structure to retrieve assets, stacks, or groups using the multi-layer indexing system; log interactions between Al platforms and assets in the Al interaction repository; and monitor asset usage and enforcing licensing terms using the dynamic licensing mechanism.

32. A method comprising: receiving digital assets and organizing them into a hierarchical structure of assets, stacks, and groups; generating and updating metadata tags dynamically based on asset type, content, and usage; logging interactions between assets and Al systems; retrieving assets using a multi-layer indexing system; and35184623667.1(PATENT) monitoring asset usage and enforcing dynamic licensing terms.

33. The method of claim 32, further comprising: validating and correcting metadata using automation tools.

34. The method of claim 32, further comprising: propagating updates in real time across the hierarchy.

35. The method of claim 32, further comprising: controlling access using hashed identifiers and role-based permissions.

36. The method of claim 25, said querying the hierarchical data structure to retrieve assets, stacks, or groups using the multi-layer indexing system, wherein when a query gets a hit at a higher level (stack, group, or universe), an additional search is triggered, and wherein said additional search is either deeper within a container to find related assets / stacks, or zoomed out to find related parent containers.

37. The system of claim 31 , said querying the hierarchical data structure to retrieve assets, stacks, or groups using the multi-layer indexing system, wherein when a query gets a hit at a higher level (stack, group, or universe), an additional search is triggered, and wherein said additional search is either deeper within a container to find related assets / stacks, or zoomed out to find related parent containers.

38. The system of claim 1 , where said stacks comprise any of temporal stacks organized by time segments and vertical stacks, wherein a temporal stack can contain relationships to multiple vertical stacks, and wherein each vertical stack has an index correlating to its position on a timeline.

39. The system of claim 9, wherein a level that was actually queried and how the asset was reached is tracked whether by direct asset query, through a stack, through a group, or through a universe.36184623667.1

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