Description:FIELD
The present invention relates generally to the field of cloud computing and media content creation. More specifically, it pertains to a unified, cloud-native platform that integrates storage, virtualized workstations, workflow tools, and artificial intelligence to provide a seamless, end-to-end post-production solution.
BACKGROUND
The process of post-production in education industry, media and entertainment, which includes tasks like video editing, color grading, visual effects (VFX), and sound mixing, has traditionally been conducted in on-premise studios. These studios require significant capital expenditure (CAPEX) for high-end computing hardware, specialized software licenses, and secure physical infrastructure. This model suffers from several major drawbacks. It is investment-intensive, leads to low hardware utilization (often as low as 50%), and lacks flexibility, requiring creative talent to be physically present at the studio.
Furthermore, traditional workflows are often inefficient and unsecure. Teams are frequently siloed, and collaboration relies on a patchwork of generic, unsecure tools like email and consumer messaging applications for sharing files and feedback. This fragmentation leads to significant productivity loss, with critical time wasted on transferring large media files between different systems and locations, a process that can take hours. Data security is another major concern, as pre-air content is highly valuable, and fragmented workflows create multiple points of vulnerability.
With the advent of cloud computing, some of these challenges have been partially addressed. Companies may use separate cloud storage providers, virtual machine (VM) providers, and software-as-a-service (SaaS) collaboration tools. However, this fragmented cloud approach introduces its own set of problems. The primary issue is the "data transfer bottleneck." A user must typically download media assets from a cloud storage service, upload them to a separate cloud-based virtual workstation for processing, and then transfer the results back to storage or to another service for review. These multiple upload/download cycles are time-consuming and negate many of the efficiency gains promised by the cloud.
Moreover, this fragmented approach fails to provide a truly integrated or seamless experience. Users must manage multiple accounts, logins, and billing systems. Security policies are inconsistent across different services, and there is no unified environment for project management or AI-driven automation. The data remains siloed in different cloud services, limiting the potential for advanced AI tools that require seamless access to the entire data pipeline.
Conventional cloud-based editing platforms use AI features while using systems for deploying virtual workstations or collaborative tools. However, integration of a centralized content storage system, an on-demand marketplace of pre-loaded turnkey virtual systems, integrated project management and collaboration workflows, and a built-in AI engine, all within a single, browser-accessible platform designed to eliminate data transfer bottlenecks is not known.
Therefore, there exists a long-standing and unmet need for a technical solution that reimagines the entire post-production workflow by providing a truly unified, end-to-end, cloud-native platform that solves the interconnected problems of productivity, cost, flexibility, and security.
OBJECTS
Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as follows:
An object of the present disclosure is to provide a cloud based platform to obviate the drawback of conventional cloud-native production system.
Another object of the project disclosure is to provide a cloud-native production system with improved data accessibility.
Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.
SUMMARY
The present invention provides a technical solution to the aforementioned problems by proposing a cloud-native, end-to-end post-production platform. The platform is distinguished by its holistic integration of all essential post-production components into a single, unified system accessible to a user via a standard web browser.
In one embodiment, the platform comprises a centralized content storage system, a virtualization layer, a suite of integrated cloud-native workflow tools, and an integrated artificial intelligence (AI) engine.
The centralized content storage system is configured to act as a single source of truth for all project data, including raw footage, intermediate versions, final files, and project management data.
The virtualization layer is operably and directly connected to the centralized content storage system. The virtualization layer features a configurable marketplace of pre-loaded, turnkey virtual systems. Each turnkey virtual system includes both virtual hardware resources (e.g., CPU, GPU, RAM) and one or more professional post-production software suites. This unique integration allows users to spin up a complete, ready-to-use virtual workstation on-demand and process media assets from the centralized storage without any intermediate data transfer steps, thereby solving the critical data transfer bottleneck.
The integrated cloud-native workflow tools provide functionalities for real-time collaboration, review and approval, project management, analytics, and security, all within the same platform environment. This overcomes the inefficiencies and security risks of using disparate third-party tools.
The integrated AI engine has seamless access to data across the entire platform, including the storage system and workflow tools. This unified data access enables the development and execution of complex, AI-driven workflows, such as automated dubbing ("ProDub"),automated timeline generation, incorporate user feedback automatically into video via prompts (in collaboration workflows), automatic creation of Look-up Tables (LUTs) / (Creative task of Color Grading) or automatic rotoscoping (Creative task of VFX), which would be impractical in a fragmented or siloed data environment.
In an embodiment, the system may also execute AI driven workflows such as semi-automated dubbing ("ProDub") and semi-automated timeline generation.
A method for providing this workflow is also disclosed. The method involves providing access to the integrated components—storage, virtualization, workflow tools, and AI—through a single, unified interface via a web browser, allowing a user to manage and execute an entire post-production project from start to finish within one seamless ecosystem. The method further includes features like usage-based pricing for the virtual systems as well as AI based workflows and the application of a comprehensive security policy across all platform components.
The synergistic effect of this holistic integration provides a non-obvious technical advantage, creating a new operational and economic model for post-production that was not previously possible with on-premise or fragmented cloud solutions.
BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 illustrates a schematic block diagram of the architecture of the cloud based post-production platform, in accordance with an embodiment of the present invention; and
Figure 2 illustrates a method for performing post-production using a cloud based post -production platform in accordance with an embodiment of the present disclosure.
LIST OF REFERENCE NUMERALS
100 platform
101 a user
102 web browser
110 content storage system
120 virtualization layer
122 turnkey virtual system
130 workflow tools
140 AI engine

DETAILED DESCRIPTION
The present invention will now be described in detail with reference to the accompanying drawing.
Referring to FIG. 1, a schematic diagram illustrates the architecture of the cloud-native post-production platform 100. The platform 100 is designed as a single, unified system accessible by a user 101 via a web browser 102 over a network. The platform 100 holistically integrates components such as a centralized content storage system 110, a virtualization layer 120, a suite of integrated cloud-native workflow tools 130, and an integrated artificial intelligence (AI) engine 140.
In an embodiment, the centralized content storage system 110 serves as the single, integrated repository for all media assets and project data. This includes, but is not limited to, raw camera footage, intermediate renders, final output files, audio tracks, graphics, and ancillary data such as project files and metadata. By centralizing all data, the system 110 eliminates data silos and provides a single source of truth for all post-production activities. All other components of the platform 100 have direct, high-speed access to the data within the storage system 110.
In an embodiment, the virtualization layer 120 is a core inventive component of the platform 100. It is operably and directly connected to the centralized content storage system 110. The virtualization layer 120 provides users 101 with access to a configurable marketplace of pre-loaded, turnkey virtual systems 122.
Unlike conventional VM providers that offer blank operating systems, a turnkey virtual system 122 is a complete, ready-to-use post-production environment. It comprises both virtual hardware resources (e.g., specified amounts of CPU, GPU, RAM) and is pre-loaded and pre-configured with one or more professional post-production software suites (e.g., Adobe Premiere Pro, Avid Media Composer, DaVinci Resolve).
The user 101 can browse the marketplace and select and instantiate a turnkey virtual system 122 on-demand, based on the specific requirements of their task. The direct connection to the storage system 110 is critical: it enables the instantiated virtual system 122 to mount and access media assets from the storage 110 as if they were on a local drive. This configuration completely eliminates the need for separate, time-consuming data upload/download cycles between storage and the computational environment, thus solving the data transfer bottleneck.
In one embodiment, access to and use of these virtual systems 122 is based on a usage-based pricing model. The platform 100 monitors the consumption of resources (e.g., time, CPU/GPU hours) and bills the user accordingly. This converts the high CAPEX of on-premise hardware into a flexible operating expense (OPEX), solving the problems of high upfront investment and low hardware utilization.
In an embodiment, the platform 100 includes a comprehensive suite of integrated cloud-native workflow tools 130. These tools are not separate third-party services but are built into the platform itself. They include:
● Real-time Collaboration Tools: Allowing multiple users to work on the same project simultaneously, share feedback, and make annotations directly on media.
● Project Management Tools: For creating projects, assigning tasks, tracking progress, and managing media assets associated with specific tasks.
● Review and Approval Tools: Providing a structured workflow for stakeholders to review content and provide formal approval or rejection.
● A Unified Security and Access Control Framework: This framework provides a single point of control for managing user permissions across the entire platform, including access to specific files in the storage system 110, rights within the collaboration tools, and access to the virtual systems 120. This provides a significant security improvement over fragmented systems.
In an embodiment, the platform 100 is built to be "AI-first." The integrated AI engine 140 has seamless, high-speed access to the unified data environment created by the platform's architecture. Because data from storage 110, workflows 130, and user interactions are all accessible, the AI engine 140 can perform complex, context-aware tasks. This enables the development and integration of advanced AI-driven workflows such as:
● Automated Dubbing ("ProDub"): Automatically generating dubbed audio tracks in multiple languages.
● Automated Timeline Generation ("Editing Agents"): Analyzing raw footage and automatically creating a rough cut or assembly edit based on scripts or other inputs.
● Intelligent Content Analysis: Automating tasks like scene detection, object recognition, and metadata tagging.
● The unified architecture serves as a foundational requirement for these complex, agentic AI workflows, which would be impractical to implement in an environment with siloed data.
In an embodiment, the system may also execute AI driven workflows such as semi-automated dubbing ("ProDub"), semi-automated timeline generation, incorporate user feedback automatically into video via prompts (in collaboration workflows), automatic creation of Look-up Tables (LUTs) / (Creative task of Color Grading) and automatic rotoscoping (Creative task of VFX).
Figure 2 shows a method for providing an end-to-end, cloud-based post-production workflow. First step 1 of the method comprises providing a centralized content storage system 110 for storing raw, intermediate, and final media assets in a single repository. A step S2 comprises providing a virtualization layer 120 directly connected to the storage system 110 such that the virtualization layer 120 includes a configurable marketplace of pre-loaded, turnkey virtual systems 122 comprising virtual hardware and at least one professional software suite. A step 3 comprises providing a suite of integrated cloud-native workflow tools 130 for project management and real-time collaboration. A step 4 comprises providing an integrated AI engine 140 with seamless access to data across the storage system and workflow tools for automating post-production tasks and final step 5 comprises enabling a user 101 to access, configure, and operate the centralized content storage system 110, the virtualization layer 120, the workflow tools 130, and the AI engine 140 through a single, unified interface via a web browser 102.
In an embodiment, the method comprises a step of processing a media asset stored in the centralized content storage system 110 using an instantiated turnkey virtual system 122 without an intermediate step of transferring the media asset from the storage system 110 to a separate virtual machine environment.
In an embodiment, the method comprises the steps of monitoring consumption of a user 101 of resources within an instantiated turnkey virtual system 122, and billing the user based on the monitored consumption.
In an embodiment, the method comprises the step of applying a single, comprehensive security policy to control access to the rights of the user 101 across the centralized content storage system 110, the workflow tools 130, and the turnkey virtual systems 122.
In an embodiment, the platform 100 architecture is configured to break down data silos between storage 110, virtual workstations, and workflow tools 130, thereby creating a unified data environment that serves as a foundational requirement for the development and execution of complex, agentic AI workflows.
The present disclosure provides a comprehensive, cloud-based platform designed to streamline and manage the entire lifecycle of media production and post-production projects. The system addresses the inefficiencies, security vulnerabilities, and fragmented collaboration inherent in traditional media workflows by offering an integrated, secure, and efficient environment. It encompasses a generic user journey that begins with secure user login via a web-browser based GUI, followed by project setup and access control where team onboarding, role-based permissions, and task allocation are established. Media assets are then ingested from various sources like cameras and external storage into a central Postudio Cloud Storage, where they are organized. The platform facilitates creative or AI task execution by allowing users to select and utilize virtualized infrastructure or AI tools for processing. Crucially, it supports live collaboration among team members, enabling iterative reviews and final approvals. Once tasks are completed and assets are approved, the system handles data transfer and asset publishing to external platforms such as Media Asset Management tool (MAMs), Over the Tops (OTTs), TV broadcasters, and archives. Throughout this process, robust security and compliance measures, including user authentication, role-based access, watermarking, encryption, auditing, and adherence to relevant certifications like ISO and TPN, are maintained. Furthermore, the platform provides step-wise data analytics, powering detailed usage and performance dashboards to enable actionability and informed decision-making.
Beyond the generic user journey, the platform is designed to support distinct workflows tailored for various professional roles, as illustrated by specific journeys for an Operations Professional (e.g., Post Production Head) and a Creative Professional (e.g., Editor). The Operations Professional's workflow focuses on project creation, defining deliverables, tasks, and deadlines; onboarding team members and setting role-based permissions; configuring data ingest from diverse sources and ensuring file organization; orchestrating complex workflows by configuring tasks and allocating resources; monitoring and overseeing task progress, workload distribution, and adherence to deadlines; setting up role-based access control and conducting audit reports for security and compliance; and finally, overseeing final delivery by approving formats and triggering publishing. In contrast, the Creative Professional's workflow emphasizes creative execution and collaboration, starting with secure login and joining assigned projects with pre-set permissions. This role involves accessing rushes or raw media files that automatically appear via camera-to-cloud or external ingest and browsing organized clips within the Postudio interface. Creative tasks are then executed using accessible creative and AI tools, with all computational resources automatically provided, often with AI assistance to boost productivity. Real-time feedback is facilitated through direct collaboration within Postudio. The process includes a review and iteration loop where output files are shared for feedback, team members provide frame-accurate comments with annotations, and the creator iterates until approval. Finally, the Creative Professional exports the final master in required formats, closing the task, while other team members handle the subsequent publishing and archiving.
The key advantages of the present system include its centralized cloud platform for improved accessibility and scalability, robust granular role-based access control for enhanced security, automated ingest and organization for efficiency, integrated AI and virtualized infrastructure for advanced creative tasks, and enhanced collaboration features like live interaction and iterative reviews. It offers comprehensive security and compliance through built-in features and adherence to industry standards, along with actionable analytics for data-driven decision-making. The system provides tailored user experiences for different professional roles and manages the entire media project lifecycle end-to-end, thereby eliminating the need for multiple disconnected tools and significantly improving efficiency, security, and collaborative capabilities in media production and post-production.
The foregoing disclosure has been described with reference to the accompanying embodiments which do not limit the scope and ambit of the disclosure. The description provided is purely by way of example and illustration.
The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
The foregoing description of the specific embodiments so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
Throughout this specification the word “comprise”, or variations such as “comprises” or “comprising”, will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps.
The use of the expression “at least” or “at least one” suggests the use of one or more elements or ingredients or quantities, as the use may be in the embodiment of the disclosure to achieve one or more of the desired objects or results.
Any discussion of documents, acts, materials, devices, articles or the like that has been included in this specification is solely for the purpose of providing a context for the disclosure. It is not to be taken as an admission that any or all of these matters form a part of the prior art base or were common general knowledge in the field relevant to the disclosure as it existed anywhere before the priority date of this application.
While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation. , Claims:We Claim:
1. A cloud-native post-production platform (100), comprising:
a centralized content storage system (110) configured to store a plurality of media assets including raw, intermediate, and final project data within a single, integrated repository accessible to all platform components;
a virtualization layer (120) operably and directly connected to the centralized content storage system (110), the virtualization layer (120) comprising a configurable marketplace of pre-loaded, turnkey virtual systems, wherein each turnkey virtual system comprises both virtual hardware resources and at least one professional post-production software suite;
a suite (130) of integrated cloud-native workflow tools, including tools for real-time collaboration and project management, accessible through the platform; and
an integrated artificial intelligence (AI) engine 140 configured to seamlessly access data from the centralized content storage system (110) and the workflow tools (130) to enable and automate AI-driven post-production tasks;
wherein the platform (100) is configured to provide a user (101) with an end-to-end post-production workflow through a single, unified interface accessible via a web browser (102).

2. The platform (100) of claim 1, wherein the direct operable connection between the centralized content storage system (100) and the virtualization layer (120) is configured to enable processing of media assets by the turnkey virtual systems without requiring separate data upload or download cycles between the storage system and the virtual systems.

3. The platform of claim 1, wherein the configurable marketplace is configured to allow the user to select and instantiate a turnkey virtual system (122) on-demand, based on the requirements of a specific post-production task.

4. The platform of claim 1, wherein the platform is configured to monitor the usage of the instantiated turnkey virtual systems (122) and provide access based on a usage-based pricing model.

5. The platform of claim 1, wherein the integrated cloud-native workflow tools (130) comprise a unified security and access control framework that governs user (101) access to the centralized content storage system (110), the collaboration tools, and the turnkey virtual systems.

6. The platform of claim 1, wherein the integrated cloud-native workflow tools (130) comprise built-in tools for review and approval processes and project analytics.

7. The platform of claim 1, wherein the AI-driven post-production tasks enabled by the AI engine (140) include at least one of: automated dubbing, automated editing timeline generation, incorporate user feedback automatically into video via prompts (in collaboration workflows), automatic creation of Look-up Tables (LUTs) / (Creative task of Color Grading) or automatic rotoscoping (Creative task of VFX).

8. A method (200) for providing an end-to-end, cloud-based post-production workflow, the method (200) comprising:
providing (S1) a centralized content storage system (110) for storing raw, intermediate, and final media assets in a single repository;
providing (S2) a virtualization layer (120) directly connected to the storage system (110), the virtualization layer (120) including a configurable marketplace of pre-loaded, turnkey virtual systems comprising virtual hardware and at least one professional software suite;
providing (S3) a suite of integrated cloud-native workflow tools (130) for project management and real-time collaboration;
providing (S4) an integrated AI engine (140) with seamless access to data across the storage system (110) and workflow tools (130) for automating post-production tasks; and
enabling (S4) a user (101) to access, configure, and operate the centralized content storage system (110), the virtualization layer (120), the workflow tools (130), and the AI engine (140) through a single, unified interface via a web browser (102).

9. The method (200) of claim 8, comprises a step of processing a media asset stored in the centralized content storage system (110) using an instantiated turnkey virtual system without an intermediate step of transferring the media asset from the storage system (110) to a separate virtual machine environment.

10. The method (200) of claim 8, comprises the steps of:
monitoring consumption of the user (101) of resources within an instantiated turnkey virtual system; and
billing the user (101) based on the monitored consumption.

11. The method (200) of claim 8, comprises a step of applying a single, comprehensive security policy to control a user's (101) access rights across the centralized content storage system (110), the workflow tools (130), and the turnkey virtual systems.

12. The platform (100) of claim 1, wherein the platform architecture is configured to break down data silos between storage, virtual workstations, and workflow tools, thereby creating a unified data environment that serves as a foundational requirement for the development and execution of complex, agentic AI workflows.