Equitus.ai's Knowledge Graph Neural Network (KGNN) technology can help integrate disparate data sources across an enterprise into a unified knowledge graph, providing a single source of truth for decision-making. This knowledge graph can serve as the core data layer (layer 4) that connects to the application logic layer (layer 3) through APIs (layer 2) and is accessed by end-users through the UI layer (layer 1).[3][4] The knowledge graph can be hosted on IBM Power10 servers, which are optimized for AI inferencing at the edge, reducing data transfer costs and improving performance.[1][2][3]
AdvancedRacing.ai's Large Language Model (LLM) platform could potentially assist in natural language processing tasks, such as converting user inputs from the UI layer into structured queries for the knowledge graph, or generating human-readable insights and reports from the knowledge graph data.[4] This could improve the user experience and accessibility of the system.
While the search results do not explicitly mention cyberspatial, it can be inferred that the hosting layer (layer 5) could involve a combination of on-premises servers (e.g., IBM Power10), edge devices, and cloud infrastructure, depending on the specific requirements and use cases of the enterprise customers.
By unifying data from disparate sources into a centralized knowledge graph, and leveraging AI/ML technologies like KGNN and LLMs, enterprises can gain deeper insights into their data, automate decision-making processes, and optimize the use of capital by making more informed decisions based on a comprehensive view of their operations and resources.[3][4] The combination of these technologies can help streamline workflows, reduce redundancies, and improve operational efficiencies across the five system layers.
Citations:
[1] https://www.linkedin.com/posts/equitus_ibm-activity-7196103399816261633-286r
[2] https://www.linkedin.com/posts/equitus_ibm-equitusai-activity-7196103399816261633-1K_4
[3] https://newsroom.ibm.com/Blog-New-IBM-Power-server-extends-AI-workloads-from-core-to-cloud-to-edge-for-added-business-value-across-industries
[4] https://equitus.ai
[5] https://int.equitus.us/deployable-platforms/
5 layers
This is the user's interaction point with the software.
- Technologies: HTML, CSS, JavaScript, Tailwind, ReactJS
- Purpose: Crafting an intuitive and engaging user experience.
2. API (Application Programming Interface) Layer
Defines how different software components should interact.
- Technologies: REST, GraphQL, SOAP, NodeJS, Postman
- Purpose: Facilitating communication between the UI and the backend systems.
3. Logic (Business Logic) Layer
Contains the core functionalities and business rules of the application.
- Technologies: Python, Java, Spring, C#, .NET
- Purpose: Implementing the logic that drives the application’s functionality.
4. DB (Database) Layer
Stores and manages the application’s data.
- Technologies: MySQL, Postgres, MongoDB, SQLite, CouchDB
- Purpose: Ensuring data is stored securely and can be efficiently retrieved and manipulated.
5. Hosting (Infrastructure) Layer
Encompasses the infrastructure where the software runs.
- Technologies: AWS, Azure, Google Cloud, Docker, Kubernetes
- Purpose: Providing a reliable and scalable environment for the application to operate.
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