AI CONTROL INFRASTRUCTURE
Stopping one model endpoint does not stop an AI system. A complete shutdown capability requires inventory, independent authority, graduated intervention, cross-system propagation, operational continuity, evidence preservation, and verified recovery. Decision Hypervisor provides the control layer.
Model-independent · Vendor-neutral · SaaS, VPC, on-premises or air-gapped
AI systems are distributed across models, agents, tools, credentials, APIs, clouds, data stores, and physical systems. A complete control system must address every layer.
Stop inference at model endpoints. Necessary but insufficient — agents may continue executing previously authorized actions.
Terminate autonomous software, revoke tool access, credentials, network connections, and queued actions across the agent fleet.
Suspend specific users, accounts, or use patterns without affecting the entire platform.
Disable individual tools, connectors, data access, or high-risk capabilities while maintaining core operations.
Reduce inference rates, token budgets, compute allocation, or concurrency to limit system capacity proportionally.
Block external egress, revoke delegated authority, and prevent lateral movement across environments.
A model cannot be the final authority over whether it is monitored, restricted, suspended, or shut down. The control layer must be structurally independent of the reasoning system it governs.
Models and agents. They propose, plan, reason, and request actions. They should not determine the boundaries of their own authority.
Decision Hypervisor. Independent credentials, separate administrative domain, out-of-band channels. Evaluates authority, applies policy, enforces intervention.
Tools, infrastructure, data, and machinery. Every consequential action flows through the control plane before reaching this layer.
An intervention that cannot be verified cannot be trusted. Every affected component must acknowledge enforcement. Unacknowledged components represent control gaps.
Authority validation
Order signed and authorized
Provider adapters
Instructions dispatched
Model endpoints
Throttled or stopped
Agent runtimes
Suspended or terminated
Tool gateways
Access revoked
Credentials
Invalidated
Network controls
Routes isolated
Verification probes
Independent confirmation
A blunt shutdown can create a second emergency. Control architecture must include continuity — transitioning critical operations to an approved fallback before or during containment.
Roll back to a known-safe model checkpoint.
Route to a different model provider or service.
Deterministic logic that does not depend on AI inference.
Route decisions to trained human operators.
Maintain visibility while preventing all mutations.
Accept requests but defer execution until control is restored.
Restrict to specific regions or jurisdictions.
Transition physical systems to a known-safe operating state.
Do not merely issue a shutdown order. Prove it was executed. Recovery must be governed as carefully as shutdown — an unauthorized reactivation can reintroduce the original risk.
Decision Hypervisor is the independent execution-control layer positioned between autonomous intelligence and consequential action.
Every consequential action is evaluated before it reaches tools, APIs, databases, or infrastructure.
Six decision states from Authorized through Denied, with modification, escrow, human review, and routing.
Unresolvable policies deny by default. The system does not fail open.
SHA-256 hash-chained, append-only decision traces provide tamper-evident forensic records.
Bounded authority grants, delegation chains, jurisdiction scoping, and time-limited execution tokens.
Any decision can be reconstructed exactly as it occurred for incident investigation and verification.
Identify control gaps before an incident, regulator, customer, insurer, or board member asks.
Intelligence proposes. Authority decides. Control remains human.