System Scope and Context
Business Context
The Agentic Layer operates within a broader enterprise ecosystem, serving as a control plane that coordinates AI agents and manages their interactions with external systems. The system is designed to integrate into existing enterprise infrastructure rather than to replace it, providing AI orchestration capabilities while maintaining organizational sovereignty over data and operations.
System Boundary
The Agentic Layer Platform Boundary defines the scope of components under direct control of the AI orchestration system. This includes all Kubernetes-native components for agent management, AI gateway services, governance tools, and operational interfaces. External systems maintain their independence while benefiting from standardized AI integration patterns.
External Actors and Systems
External Frontends
Web, mobile, and other user interfaces that provide user-facing applications leveraging AI capabilities. These frontends connect to the Agentic Layer via the OpenAI Chat Completion API to access coordinated AI services while maintaining their own user experience and business logic.
External Agents
AI agents running outside the platform that need to integrate with or leverage the centralized AI orchestration capabilities. These agents connect to the Agentic Layer via the A2A (Agent-to-Agent) protocol, enabling standardized inter-agent communication. They may include existing AI systems, specialized agents, or third-party AI services that benefit from the governance and routing provided by the Agentic Layer.
Apps
Applications that leverage AI capabilities through the AG-UI protocol. This protocol provides a standardized interface for applications to interact with AI agents and services managed by the Agentic Layer.
External Tool Servers
External tools and services that AI agents can access through the MCP (Model Context Protocol). These tool servers provide capabilities such as database access, file operations, API integrations, and other services that agents can invoke during task execution. The Agentic Layer’s Tool Gateway manages these connections.
LLM Providers
External Large Language Model providers such as OpenAI, Google Gemini, Anthropic Claude, and other AI service providers. The Agentic Layer abstracts differences between these providers through the AI Gateway component. Additionally, locally deployed language models can be used as an alternative to cloud-based providers.
System Interactions
External System Connectivity
External systems interact with the Agentic Layer through protocol-specific entry points:
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Via OpenAI Chat Completion API: External Frontends send requests using the widely adopted OpenAI Chat Completion API standard
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Via A2A: External Agents communicate using the Agent-to-Agent protocol for standardized agent interoperability
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Via AG-UI: Apps connect through the AG-UI protocol for application-level AI integration
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Via MCP: The Agentic Layer connects to External Tool Servers via the Model Context Protocol for tool access
AI Service Integration
The Agentic Layer orchestrates AI interactions by:
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Sending prompts and receiving results from LLM providers through the AI Gateway
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Providing unified access to multiple AI service providers with intelligent routing and failover
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Supporting both cloud-based and locally deployed language models
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Managing authentication, rate limiting, and usage tracking across providers
Technical Context
The Agentic Layer serves as an integration hub rather than a data repository. It orchestrates interactions between various systems while maintaining clear separation of concerns:
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Stateless Operations: The platform focuses on coordination and routing rather than data storage
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API-First Integration: All interactions occur through well-defined APIs and standard protocols (A2A, MCP, AG-UI, OpenAI Chat Completion API)
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Kubernetes-Native Deployment: All components leverage Kubernetes primitives for scaling, service discovery, and operational management