AWS Details Pluggable Seven-Layer Enterprise Agentic AI Architecture
AI assistants · Enterprise AI · Cybersecurity and privacy
AWS published a seven-layer reference framework on Amazon Bedrock AgentCore to bridge the gap between prototypes and production-scale enterprise multi-agent AI systems.
AWS introduced the Pluggable Agentic AI Framework, a seven-layer composable reference architecture built to help enterprises move multi-agent AI applications from early prototypes into production scale. The architecture divides system responsibilities into Data and Knowledge, Model and Inference, Orchestration, Security and Guardrails, Application, Observability, and Agentic Operations. AWS noted that the design relies on stable contracts between layers, enabling organizations to replace individual building blocks with alternative tools and services as requirements evolve.
Key takeaways
- The framework establishes seven modular layers ranging from data retrieval and model routing to centralized orchestration and continuous evaluation.
- Orchestration patterns emphasize supervisor agents delegating tasks to bounded specialist agents using standardized protocols like MCP and A2A.
- Security controls mandate fine-grained authorization, scoped temporary credentials, data masking, and tamper-evident audit trails at every layer.
- A reference implementation demonstrates the pattern using a retail customer support workflow with supervisor routing and specialist agents.
Source：AWS Machine Learning Read the original ↗
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