MULTI-USER ACCESS SYSTEM FOR ARTIFICIAL INTELLIGENCE ALGORITHMS

Abstract

ABSTRACT Multi-User Access System for Artificial Intelligence Algorithms The present disclosure introduces multi-user access system for artificial intelligence algorithms 100. It provides a collaborative platform that democratizes access to AI technologies. The system features a user interface 102 for interaction, supported by backend infrastructure 104 for data processing. AI algorithm repository 106 offers pre-built models, with access through role-based access control system 108 and secured through authentication and security module 110. Users collaborate via collaborative workflow tools 112 and the collaborative algorithm development environment 114, with changes tracked through collaboration with version synchronization 144. The secure data sandbox 118 allows safe testing of models, monitored through real-time performance monitoring and analytics 120. The integration layer 122 ensures interoperability with external systems, while the customizable algorithm experimentation framework 130 and modular algorithm design 132 enhance flexibility. AI-driven recommendations and support are provided by module 124, with insights from advanced predictive analytics 142, ensuring optimized workflows and decision-making. Reference Fig 1

Specification

Description:Multi-User Access System for Artificial Intelligence Algorithms
TECHNICAL FIELD
[0001] The present innovation relates to a multi-user platform that enables secure, collaborative access and management of artificial intelligence (AI) algorithms.

BACKGROUND

[0002] The rapid growth of artificial intelligence (AI) technologies has transformed industries by enabling data-driven insights and automation. However, the adoption of AI across sectors such as healthcare, finance, education, and manufacturing is hindered by several challenges. Traditionally, access to AI algorithms and models is restricted to experts, such as data scientists and engineers, who possess the necessary technical expertise. This creates a gap between AI developers and end-users, limiting the potential for broader applications and innovation. Existing systems include proprietary platforms and open-source frameworks that provide access to AI models, but these options present significant drawbacks. Proprietary platforms are often expensive, lack flexibility, and restrict customization, while open-source frameworks demand technical expertise and offer limited collaborative features, making it difficult for non-experts to leverage AI effectively.
[0003] Moreover, many existing platforms fail to provide robust collaboration tools, resulting in disjointed workflows and inefficiencies when multiple users attempt to work on the same project. Security and privacy concerns are also prevalent, as most platforms do not offer adequate role-based access control or data encryption, leading to potential risks of unauthorized access and data breaches. The absence of these critical features complicates compliance with data protection regulations, particularly in sensitive sectors like healthcare and finance.
[0004] The proposed invention overcomes these challenges by introducing a multi-user access system for ai algorithms that democratizes access to AI technologies through a secure, user-friendly, and collaborative platform. Unlike existing solutions, this system offers dynamic role-based access control, multi-factor authentication and real-time collaborative workflows with version control. The invention's novelty lies in its seamless integration with third-party systems, customizable dashboards, and AI-driven recommendations, ensuring both technical and non-technical users can effectively engage with AI models. By addressing the limitations of current platforms and providing a secure, scalable environment, the invention empowers organizations to unlock the full potential of AI technologies across diverse sectors while ensuring compliance, collaboration, and accessibility.

OBJECTS OF THE INVENTION

[0005] The primary object of the invention is to provide secure, multi-user access to AI algorithms through dynamic role-based access control, ensuring users only access relevant resources based on their roles.

[0006] Another object of the invention is to enhance collaboration by enabling multiple users to work simultaneously on AI models with real-time version control, shared workspaces, and feedback mechanisms.

[0007] Another object of the invention is to simplify user onboarding with a user-friendly interface, AI-guided workflows, and customizable dashboards, making AI technologies accessible to non-technical users.

[0008] Another object of the invention is to promote data security and privacy through multi-factor authentication, single sign-on, and data encryption for both stored and transmitted data.

[0009] Another object of the invention is to support seamless integration with existing business intelligence tools and external systems through API connectivity, enhancing interoperability and workflow efficiency.

[00010] Another object of the invention is to reduce the risk of resource mismanagement by incorporating AI-driven recommendations for algorithm selection, parameter tuning, and workflow optimization.

[00011] Another object of the invention is to offer modular algorithm design, allowing users to create, customize, and reuse algorithm components across different projects, fostering faster innovation.

[00012] Another object of the invention is to ensure ethical compliance by integrating automated compliance checks that monitor algorithms for biases and adherence to regulatory standards.

[00013] Another object of the invention is to provide a secure sandbox environment for testing AI models with sensitive datasets, allowing safe experimentation without impacting production environments.

[00014] Another object of the invention is to empower organizations to make data-driven decisions by providing real-time performance monitoring tools with actionable insights and predictive analytics for model refinement


SUMMARY OF THE INVENTION

[00015] In accordance with the different aspects of the present invention, multi-user access system for artificial intelligence algorithms is presented. It provides a secure, collaborative platform for multi-user access to AI algorithms, featuring dynamic role-based access control, real-time version control, and AI-guided workflows. It enables seamless integration with existing systems through APIs and ensures data security with multi-factor authentication and encryption. Users can develop, customize, and reuse modular AI components, promoting faster innovation. A secure sandbox environment allows safe experimentation with sensitive data, while AI-driven recommendations optimize workflows and performance. The system democratizes access to AI technologies, empowering organizations across various sectors to make data-driven decisions efficiently and ethically.

[00016] Additional aspects, advantages, features and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments constructed in conjunction with the appended claims that follow.

[00017] It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.

BRIEF DESCRIPTION OF DRAWINGS
[00018] The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.

[00019] Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:

[00020] FIG. 1 is component wise drawing for multi-user access system for artificial intelligence algorithms.

[00021] FIG 2 is working methodology of multi-user access system for artificial intelligence algorithms.

DETAILED DESCRIPTION

[00022] The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognise that other embodiments for carrying out or practising the present disclosure are also possible.

[00023] The description set forth below in connection with the appended drawings is intended as a description of certain embodiments of multi-user access system for artificial intelligence algorithms and is not intended to represent the only forms that may be developed or utilised. The description sets forth the various structures and/or functions in connection with the illustrated embodiments; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimised to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.

[00024] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.

[00025] The terms "comprises", "comprising", "include(s)", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, or system that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or system. In other words, one or more elements in a system or apparatus preceded by "comprises... a" does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.

[00026] In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings and which are shown by way of illustration-specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

[00027] The present disclosure will be described herein below with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the description with unnecessary detail.

[00028] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is disclosed, in accordance with one embodiment of the present invention. It comprises of user interface 102, backend infrastructure 104, AI algorithm repository 106, role-based access control system 108, authentication and security module 110, collaborative workflow tools 112, collaborative algorithm development environment 114, data provenance and lineage tracker 116, secure data sandbox 118, real-time performance monitoring and analytics 120, integration layer 122, AI-driven user support and recommendations module 124, ethical compliance checker 126, customizable dashboards and notification system 128, customizable algorithm experimentation framework 130, modular algorithm design and customization 132, community-driven algorithm marketplace 134, NLP-based querying system 136, resource allocation and optimization system 138, knowledge repository 140, advanced predictive analytics for user behavior 142 and real-time collaboration with version synchronization 144.


[00029] Referring to Fig. 1, the present disclosure provides details of multi-user access system for artificial intelligence algorithms 100 is a secure, collaborative platform that democratizes access to AI technologies across various sectors. It offers features like dynamic role-based access control, real-time version control, multi-factor authentication, and AI-driven recommendations. It comprises of user interface 102, backend infrastructure 104, and AI algorithm repository 106, facilitating seamless interaction and data processing. Collaboration is enhanced through collaborative workflow tools 112 and the collaborative algorithm development environment 114, with secure testing ensured by the secure data sandbox 118. Real-time insights are provided by the real-time performance monitoring and analytics 120, while interoperability is enabled by the integration layer 122. Advanced tools like the customizable algorithm experimentation framework 130 and resource allocation and optimization system 138 ensure scalability, efficiency, and adaptability in AI-driven projects.

[00030] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with user interface 102 to offer users a simple and intuitive platform to interact with AI tools. In one of the embodiments, it provides dashboards, drag-and-drop functionality, and visualization tools, enabling seamless data manipulation. This interface 102 serves as the primary point of interaction, integrating with backend infrastructure 104 to process requests and display results efficiently. It also interacts with collaborative workflow tools 112 to present shared projects and version histories to the users.

[00031] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with backend infrastructure 104 to handle data processing, communication, and storage. It ensures smooth interworking between the user interface 102 and AI algorithm repository 106 by managing requests and responses. The infrastructure 104 relies on cloud services for scalability and integrates with the resource allocation and optimization system 138 to ensure efficient use of computational resources.

[00032] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with AI algorithm repository 106 that stores pre-built algorithms, models, and documentation. It offers users access to algorithms that can be deployed or customized through the collaborative algorithm development environment 114. The repository 106 interacts closely with the customizable algorithm experimentation framework 130, allowing users to experiment with various models without altering the main database.

[00033] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with role-based access control system 108 to assign specific roles and permissions to users based on their responsibilities. It dynamically manages access to AI algorithms, ensuring users only access what is relevant to their tasks. This system works closely with the authentication and security module 110 to enforce secure access and with collaborative workflow tools 112 to grant or restrict collaboration features based on roles.

[00034] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with authentication and security module 110 to ensure secure user access through multi-factor authentication (MFA) and single sign-on (SSO). It verifies user identities and encrypts data during transmission and storage. This module interacts with role-based access control system 108 to enforce security policies and with secure data sandbox 118 to ensure only authorized users can access sensitive testing environments.

[00035] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with collaborative workflow tools 112 to enhance teamwork by offering real-time collaboration features like shared workspaces and version control. These tools are integrated with collaborative algorithm development environment 114 and secure data sandbox 118 to facilitate seamless teamwork and safe testing. It also synchronizes with real-time performance monitoring and analytics 120 to track project progress and model performance.

[00036] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with collaborative algorithm development environment 114 that allows multiple users to co-develop algorithms simultaneously. It features live coding interfaces, code review tools, and conflict resolution mechanisms. This environment works closely with AI-driven user support and recommendations module 124 to assist users during development and integrates with customizable dashboards and notification system 128 for managing project updates effectively.

[00037] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with data provenance and lineage tracker 116 to monitor data sources, transformations, and modifications. It ensures transparency in AI model development and assists in regulatory compliance. This tracker 116 integrates with AI algorithm repository 106 to provide visibility into algorithm usage and with performance monitoring and analytics 120 to identify the impact of data changes on model outcomes.

[00038] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with secure data sandbox 118 to allow safe testing of AI models using sensitive datasets. This sandbox isolates testing activities from production environments, minimizing risks. It works in conjunction with collaborative workflow tools 112 to support teamwork and integrates with resource allocation and optimization system 138 to ensure efficient testing without excessive resource consumption.

[00039] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with real-time performance monitoring and analytics 120 to provide actionable insights into the performance of AI models. It tracks key metrics and offers visualizations to assist users in model optimization. This component works with customizable dashboards and notification system 128 to display performance alerts and integrates with AI-driven recommendations module 124 to suggest model improvements.

[00040] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with integration layer 122 to enable seamless connectivity with third-party platforms and tools. It ensures interoperability by supporting multiple APIs and frameworks, facilitating data exchange between external systems and AI algorithm repository 106. This layer interacts with customizable algorithm experimentation framework 130 to integrate experimental models into existing workflows efficiently.

[00041] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with AI-driven user support and recommendations module 124 to guide users in selecting appropriate algorithms and workflows. It offers suggestions based on user behavior and project requirements, enhancing usability. This module 124 works with collaborative algorithm development environment 114 to assist during development and with role-based access control system 108 to align recommendations with user roles.

[00042] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with ethical compliance checker 126 to monitor AI algorithms for biases and ensure adherence to privacy regulations. It evaluates algorithms stored in the AI algorithm repository 106 and provides alerts through the customizable dashboards and notification system 128 to notify users of potential ethical concerns.

[00043] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with customizable dashboards and notification system 128 to allow users to personalize their workspace and set alerts for project updates and performance issues. It displays key metrics from real-time performance monitoring and analytics 120 and integrates with collaborative workflow tools 112 to notify users of changes in shared projects.

[00044] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with customizable algorithm experimentation framework 130 to support A/B testing and comparative analysis of multiple models. It allows users to manage different algorithm versions and integrates with AI algorithm repository 106 for storing experimental results. This framework also interacts with secure data sandbox 118 to facilitate safe testing.

[00045] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with modular algorithm design and customization 132 to allow users to build, modify, and reuse algorithm components across projects. This feature enables faster innovation by integrating with collaborative algorithm development environment 114 and AI-driven user support module 124 to streamline customization.

[00046] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with community-driven algorithm marketplace 134 to enable users to share, sell, or exchange custom algorithms. It fosters innovation by promoting peer contributions and integrates with the AI algorithm repository 106 to facilitate the deployment of marketplace algorithms.

[00047] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with NLP-based querying system 136 to allow users to interact with the platform using natural language. This feature enhances accessibility, enabling non-technical users to query algorithms stored in the AI algorithm repository 106 and perform operations seamlessly through user interface 102.

[00048] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with resource allocation and optimization system 138 to manage computational resources like CPU, GPU, and memory. This system optimizes performance by allocating resources dynamically based on workload. It integrates with backend infrastructure 104 for efficient processing and with real-time performance monitoring and analytics 120 to track resource usage.

[00049] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with knowledge repository 140 to offer users access to tutorials, case studies, troubleshooting guides, and best practices. This repository integrates with AI-driven recommendations module 124 to provide relevant content and supports collaboration by offering learning resources through collaborative workflow tools 112.

[00050] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with advanced predictive analytics for user behavior 142 to anticipate user needs and optimize workflows. This component 142 analyzes user interactions to predict future behavior and resource demands, enhancing decision-making. It works with resource allocation and optimization system 138 to adjust resource usage proactively.

[00051] Referring to Fig. 1, multi-user access system for artificial intelligence algorithms 100 is provided with real-time collaboration with version synchronization 144 to ensure all users are working on the latest algorithm versions. It synchronizes changes in real time, preventing conflicts, and integrates with collaborative workflow tools 112 to facilitate seamless teamwork and efficient project management





[00052] Referring to Fig 2, there is illustrated method 200 for multi-user access system for artificial intelligence algorithms 100. The method comprises:

At step 202, method 200 includes user logging into the platform through the user interface 102 using multi-factor authentication provided by the authentication and security module 110;

At step 204, method 200 includes user accessing assigned algorithms and datasets based on permissions granted by the role-based access control system 108;

At step 206, method 200 includes user selecting and deploying an algorithm from the AI algorithm repository 106 through guided workflows in the collaborative algorithm development environment 114;

At step 208, method 200 includes backend infrastructure 104 processing the user's request, ensuring communication between the user interface 102 and the repository 106;

At step 210, method 200 includes multiple users collaborating in real-time using collaborative workflow tools 112, where changes are tracked and synchronized through version control with real-time collaboration with version synchronization 144;

At step 212, method 200 includes users experimenting with algorithms using the customizable algorithm experimentation framework 130, where modifications are made within the secure data sandbox 118;

At step 214, method 200 includes resource allocation and optimization system 138 dynamically managing computational resources to handle the workload efficiently;

At step 216, method 200 includes performance metrics being monitored through real-time performance monitoring and analytics 120, providing users with actionable insights via customizable dashboards and notification system 128;

At step 218, method 200 includes the AI-driven user support and recommendations module 124 analyzing user behavior to suggest relevant algorithms and improvements;

At step 220, method 200 includes the ethical compliance checker 126 evaluating the deployed algorithms for biases and regulatory adherence, alerting users through dashboards 128 if any issues are detected;

At step 222, method 200 includes users leveraging the integration layer 122 to import or export data seamlessly between external systems and the AI algorithm repository 106;

At step 224, method 200 includes users accessing additional resources and tutorials from the knowledge repository 140 to enhance their understanding and project execution;

At step 226, method 200 includes the advanced predictive analytics for user behavior 142 forecasting user needs and adjusting workflows accordingly, ensuring efficient system performance and project delivery.


[00053] In the description of the present invention, it is also to be noted that, unless otherwise explicitly specified or limited, the terms "fixed" "attached" "disposed," "mounted," and "connected" are to be construed broadly, and may for example be fixedly connected, detachably connected, or integrally connected, either mechanically or electrically. They may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.

[00054] Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as "including", "comprising", "incorporating", "have", "is" used to describe and claim the present disclosure are intended to be construed in a non- exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural where appropriate.

[00055] Although embodiments have been described with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More particularly, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the present disclosure, the drawings and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, alternative uses will also be apparent to those skilled in the art.
, Claims:WE CLAIM:
1. A multi-user access system for artificial intelligence algorithms 100 comprising of
user interface 102 to provide a platform for users to interact with the system through dashboards and visualization tools;

backend infrastructure 104 to manage data processing, communication, and storage between components;

AI algorithm repository 106 to store and provide access to pre-built algorithms and models;

role-based access control system 108 to assign user roles and permissions based on responsibilities;

authentication and security module 110 to ensure secure access through multi-factor authentication and encryption;

collaborative workflow tools 112 to enable real-time collaboration with version control and shared workspaces;

collaborative algorithm development environment 114 to support multi-user coding and development of ai models;

data provenance and lineage tracker 116 to monitor data sources, transformations, and modifications;

secure data sandbox 118 to provide a safe environment for testing models with sensitive data;

real-time performance monitoring and analytics 120 to track model performance and provide actionable insights;

integration layer 122 to ensure seamless data exchange and interoperability with external systems;

AI-driven user support and recommendations module 124 to suggest relevant algorithms and workflows based on user behavior;

ethical compliance checker 126 to monitor algorithms for biases and ensure regulatory adherence;

customizable dashboards and notification system 128 to allow users to personalize their interface and receive alerts;

customizable algorithm experimentation framework 130 to support a/b testing and version management of algorithms;

modular algorithm design and customization 132 to enable the creation and reuse of algorithm components across projects;

community-driven algorithm marketplace 134 to allow users to share, sell, or exchange custom algorithms;

NLP-based querying system 136 to enable users to interact with the platform using natural language queries;
resource allocation and optimization system 138 to manage computational resources efficiently based on workload demands;
knowledge repository 140 to provide tutorials, case studies, and best practices for user learning;

advanced predictive analytics for user behavior 142 to forecast needs and optimize workflows proactively; and

real-time collaboration with version synchronization 144 to ensure all users work on the latest version of the algorithms

2. The multi-user access system for artificial intelligence algorithms 100 as claimed in claim 1, wherein system is configured to provide secure, collaborative access to AI models through dynamic role-based access control, real-time performance monitoring, customizable algorithm experimentation, seamless interoperability with external systems, and AI-driven recommendations, ensuring efficient resource management, data privacy, and enhanced teamwork across various sectors.

3. The multi-user access system for artificial intelligence algorithms 100 as claimed in claim 1, wherein role-based access control system 108 is configured to dynamically assign roles and permissions to users based on their responsibilities and project requirements, ensuring secure and task-specific access to AI resources.

4. The multi-user access system for artificial intelligence algorithms 100 as claimed in claim 1, wherein authentication and security module 110 incorporates multi-factor authentication, single sign-on, and encryption protocols to protect data and verify user identities, ensuring secure access and data privacy.

5. The multi-user access system for artificial intelligence algorithms 100 as claimed in claim 1, wherein collaborative workflow tools 112 enable real-time collaboration through shared workspaces, version control, live commenting, and synchronized updates to facilitate teamwork on AI projects.

6. The multi-user access system for artificial intelligence algorithms 100 as claimed in claim 1, wherein customizable algorithm experimentation framework 130 is designed to support A/B testing, version management, and comparative analysis of algorithms without disrupting the main project workflow.

7. The multi-user access system for artificial intelligence algorithms 100 as claimed in claim 1, wherein secure data sandbox 118 provides an isolated environment for testing and validating AI models with sensitive datasets, ensuring data privacy and compliance with regulatory standards.

8. The multi-user access system for artificial intelligence algorithms 100 as claimed in claim 1, wherein advanced predictive analytics for user behavior 142 is designed to analyze user interactions and forecast future needs, optimizing workflows and resource allocation for efficient project management.

9. The multi-user access system for artificial intelligence algorithms 100 as claimed in claim 1, wherein real-time performance monitoring and analytics 120 configured to track AI model metrics during execution, providing actionable insights through customizable dashboards to optimize performance.

10. The multi-user access system for artificial intelligence algorithms 100 as claimed in claim 1, wherein method comprise of
user logging into the platform through the user interface 102 using multi-factor authentication provided by the authentication and security module 110;
user accessing assigned algorithms and datasets based on permissions granted by the role-based access control system 108;

user selecting and deploying an algorithm from the AI algorithm repository 106 through guided workflows in the collaborative algorithm development environment 114;

backend infrastructure 104 processing the user's request, ensuring communication between the user interface 102 and the repository 106;

multiple users collaborating in real-time using collaborative workflow tools 112, where changes are tracked and synchronized through version control with real-time collaboration with version synchronization 144;

users experimenting with algorithms using the customizable algorithm experimentation framework 130, where modifications are made within the secure data sandbox 118;

resource allocation and optimization system 138 dynamically managing computational resources to handle the workload efficiently;

performance metrics being monitored through real-time performance monitoring and analytics 120, providing users with actionable insights via customizable dashboards and notification system 128;

AI-driven user support and recommendations module 124 analyzing user behavior to suggest relevant algorithms and improvements;

ethical compliance checker 126 evaluating the deployed algorithms for biases and regulatory adherence, alerting users through dashboards 128 if any issues are detected;

users leveraging the integration layer 122 to import or export data seamlessly between external systems and the AI algorithm repository 106;

users accessing additional resources and tutorials from the knowledge repository 140 to enhance their understanding and project execution;

advanced predictive analytics for user behavior 142 forecasting user needs and adjusting workflows accordingly, ensuring efficient system
performance and project delivery.

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