AAIOS — Agentic AI Operating System
The enterprise runtime and control plane for registering, orchestrating, securing, observing and governing AI agents across data, tools and business workflows.
What this capability solves
Agentic AI moves beyond chat into actions: agents call APIs, use tools, access data, coordinate with other agents and trigger business processes. AAIOS provides the common operating layer required to keep those actions identity-aware, policy-controlled, observable, testable and recoverable.
Technology is implemented as an operating capability: architecture, integration, governance, assurance, people, procedures and measurable outcomes are designed together.
Capability model
Modular building blocks allow the scope to start with a focused pilot and expand into an enterprise operating model.
Agent Registry
Inventory agent purpose, owner, model, tools, data classes, environment, risk tier and lifecycle status.
Multi-Agent Orchestration
Plan and coordinate specialized agents, hand-offs, task graphs, retries, timeouts and deterministic workflow boundaries.
Tool & Action Gateway
Mediate tool calls through approved schemas, least privilege, validation, allow/deny policy and transaction controls.
Model & RAG Gateway
Route models and knowledge sources with policy, retrieval authorization, prompt controls, redaction and model abstraction.
Memory Control
Separate session, user, workflow and durable memory with retention, access and deletion policies.
Policy & Approval Engine
Human approval, maker-checker, risk-based gates, budgets, rate limits and business-rule enforcement before sensitive actions.
Agent Identity & Security
Workload identity, secrets management, DLP, sandboxing, network restrictions and scoped credentials.
Evaluation & Guardrails
Pre-deployment simulations, test suites, hallucination/tool-use checks, policy regression and safety scoring.
AgentOps & Observability
Traces, action logs, cost, latency, success/error rates, SLOs, incidents, kill switch and rollback.
Governance Evidence
Persist decisions, approvals, model/tool versions and action evidence into enterprise risk and audit workflows.
How the capability fits together
Final topology, control placement and deployment model are validated during discovery and detailed design.
Controls & governance
- Least-privilege agent and tool identity
- Human approval for high-impact actions
- Schema validation for every tool call
- Prompt/data leakage controls
- Memory retention and deletion policy
- Budget/rate/action limits
- Kill switch and safe rollback
- Comprehensive action provenance
Priority use cases
- Customer-service resolution agents
- Compliance/privacy workflow agents
- IT/security operations agents
- Finance/reconciliation agents
- Knowledge/research agents
- Industrial maintenance assistants
- Multi-agent business-process automation
Key deliverables
- Agent inventory and risk tiers
- Reference AAIOS architecture
- Tool/model access policy
- Approval matrix and RACI
- Evaluation suite and release gates
- AgentOps dashboard/SLOs
- Incident and kill-switch playbook
- Production operating model
Integration considerations
- Enterprise IAM/workload identity
- APIs and SaaS tools
- Data platforms and vector/RAG
- Workflow/BPM/ITSM
- SIEM/SOAR and observability
- GRC/evidence systems
- Model gateways/providers
Phased delivery
Each phase ends with evidence, acceptance criteria and a decision gate before broader scale-out.