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| # AISA β Agentic AI Systems Architecture | |
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| ## Overview | |
| AISA (Agentic AI Systems Architecture) is a system-level reference architecture | |
| for the design, deployment, evaluation, and governance of agentic AI systems. | |
| It frames agentic AI as an end-to-end system problem, addressing the | |
| architectural challenges introduced by autonomous, tool-using, | |
| and long-horizon AI behavior. | |
| --- | |
| ## Motivation | |
| As large language models evolve into persistent and goal-directed agents, | |
| key challenges increasingly arise at the system level, including: | |
| - Fragmented agent architectures | |
| - Brittle orchestration and tool usage | |
| - Limited observability and evaluation | |
| - Unclear governance and accountability | |
| AISA introduces a unified architectural model that integrates reasoning, | |
| infrastructure, evaluation, deployment, and governance. | |
| --- | |
| ## Architectural Model | |
| AISA decomposes agentic AI systems into seven high-level layers: | |
| 1. **LLM Foundation** β language understanding and reasoning | |
| 2. **Tool & Environment** β controlled external actions | |
| 3. **Cognitive Agent** β planning, goals, and memory | |
| 4. **Agentic Infrastructure** β orchestration and coordination | |
| 5. **Evaluation & Feedback** β continuous behavioral assurance | |
| 6. **Development & Deployment** β lifecycle management | |
| 7. **Governance, Ethics & Policy** β system-wide constraints | |
| This separation of concerns enables predictable behavior, | |
| continuous evaluation, and enforceable governance. | |
| --- | |
| ## System Perspective | |
| AISA treats agentic AI systems as composed, multi-layered systems | |
| whose behavior emerges from interactions across reasoning, | |
| execution, infrastructure, and policy layers. | |
| This perspective supports system-level analysis and comparison | |
| across different agentic designs. | |
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| ## Contributions | |
| This work: | |
| - Proposes a unified layered reference architecture for agentic AI systems | |
| - Clarifies responsibilities and boundaries across system components | |
| - Elevates evaluation, operations, and governance to first-class concerns | |
| - Provides a shared vocabulary for research and practice | |
| --- | |
| ## Intended Use | |
| AISA is intended for: | |
| - Research on agentic and autonomous AI systems | |
| - Design of production-grade agent architectures | |
| - Evaluation and comparison of agentic behaviors | |
| - Governance and risk analysis of deployed AI systems | |
| The framework applies to both single-agent and multi-agent systems. | |
| <h1 align="center">AISA β Agentic AI Systems Architecture</h1> | |
| <p align="center"><em>Coming soon</em></p> | |
| <p align="center"> | |
| <img | |
| src="https://cdn-uploads.huggingface.co/production/uploads/628f7a71dd993507cfcbe587/U6a8h-tFQ1s_fqayvDznl.png" | |
| alt="Agentic AI Systems Architecture (AISA)" | |
| width="320" | |
| /> | |
| </p> | |
| <p align="center"> | |
| A unified reference architecture for designing, deploying, and governing agentic AI systems. | |
| </p> | |