Runtime Control Architecture
Policies and review boards do not control agentic systems at execution time. ACR provides six operational control pillars enforced at runtime, plus a live control plane implementation with governed baseline evolution, intent-aware telemetry, protected executors, and orchestrator enforcement patterns.
Why existing governance fails
Traditional governance assumed bounded software, predictable execution, and periodic oversight. Agentic AI systems reason across steps, invoke APIs, access sensitive context, alter state, and create downstream impact at machine speed. Control must move from policy documents to runtime architecture and enforced trust paths.
Speed asymmetry
Agents act faster than humans review.
Bypass risk
If tools are reachable directly, governance is theater.
Post-hoc is too late
You need a hard stop before sensitive execution.
The enforcement boundary
Every agent action must traverse the ACR control plane before reaching execution. Identity is verified, policy is evaluated, drift is scored, and evidence is emitted — at runtime, before impact.
Agent decides to act. Emits a tool call request.
Isolated. Rollback-ready. Blast radius contained.
P6 Approval queue for high-impact actions. Escalation SLAs enforced.
P4 Append-only. Chain-of-custody. Evidence bundles per action.
If agents can reach tools without traversing the control plane, governance is theater.
The ACR control plane is not optional middleware. It is the mandatory enforcement boundary between intent and impact.
Six Control Pillars
Each pillar defines control objectives, enforcement mechanisms, evidence requirements, and test procedures. Mapped to ISO 27001, NIST CSF 2.0, ISO/IEC 42001, NIST AI RMF, and MITRE ATLAS.
Every agent attributable to a unique identity, bound to approved purpose, owner, and scope.
Runtime guardrails constraining tools, parameters, spend limits, approval gates, and execution trust paths.
Versioned behavioral baselines with approval workflows, drift scoring, and controlled promotion of a new normal.
Structured traces, append-only audit logs, evidence bundles, and intent-aware telemetry before sensitive execution.
Kill switches, sandboxing, safe-state recovery, and blast radius reduction through isolated executors.
Action tiering, approval queues, escalation SLAs, and operator-governed promotion of high-impact changes.
ACR Ecosystem
Six control pillars, standards crosswalks, control specifications, governance requirements, and implementation patterns.
Reference runtime with governed drift baselines, intent-aware telemetry, protected executors, operator console workflows, and orchestrator integration patterns.
Adversarial threat taxonomy for agentic AI. Attack surfaces, techniques, and defensive control mapping.
Start Here
Security & Architecture
Runtime control architecture, trust boundaries, failure modes, and implementation patterns for agentic AI systems.
View Architecture →GRC & Compliance
42 control mappings across ISO 27001, NIST CSF 2.0, ISO/IEC 42001, NIST AI RMF, and MITRE ATLAS.
Explore Standards Crosswalk →Engineering & Platform
Deploy ACR as the mandatory enforcement layer for sensitive actions. Route orchestrators through protected executors, evaluate actions, inspect trust paths, and export evidence bundles.
View Control Plane →Every ACR control maps to established frameworks.
42 control mappings. 5 standards. 100% pillar coverage.
The foundational paper explains the runtime control model. The live implementation shows how governed drift baselines, intent-aware telemetry, operator workflows, and protected execution work in practice.
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Framework releases, implementation guides, and community events.