Governed AI agents: controls for production
Move agents from uncontrolled experiments to governed production. Moring enforces identity boundaries, runtime policies, human-in-the-loop approvals, and immutable decision records across your models, tools and enterprise systems.
The six control layers
Identity
Every agent has a registered identity, scoped credentials, and an owner who can be called.
Permission scope
Agents reach only the systems and records their workflow needs. Read and write are separated.
Runtime policy
Deterministic rules evaluate before execution: parameter boundaries, blocked operations, spend ceilings.
Human approval
Irreversible actions pause and route to a named approver with reasoning and payload attached.
Evidence
Every run writes a tamper-evident record: prompts, model calls, tool invocations, policy decisions, approver identity.
Inventory
A registry lists every agent, its owner and its authority so there is something to review and revoke.
Regulatory alignment
Moring is built for regulated industries. The control layer maps to the requirements examiners actually ask for:
SR 26-2 (Banking)
Component-level documentation, boundary enforcement, evidence of every run with policy decisions and human approvals, named owner for each outcome.
NAIC AI Model Bulletin (Insurance)
Documentation of AI systems and their controls at the decision level, policy checks and evidence, human review recorded where required.
EU AI Act (Financial Services)
Record-keeping, human oversight, technical documentation, and risk management for high-risk AI systems.
Frequently asked questions
What controls does Moring provide for AI agents?
Six layers: identity (registered agent with scoped credentials), permission scope (read/write separation, system-level boundaries), runtime policy (deterministic rules evaluated before execution), human approval (gates for irreversible actions), evidence (tamper-evident records of every run), and inventory (agent registry with ownership and authority).
How does Moring support SR 26-2 compliance?
SR 26-2 places generative and agentic AI outside its scope, leaving your own risk management practices to answer for agents. Moring establishes the governance controls SR 26-2 expects for the systems it does cover: component-level documentation, boundary enforcement, evidence of every run with policy decisions and human approvals, and a named owner for each agent outcome.
Can Moring govern agents under NAIC AI Model Bulletin requirements?
Yes. The NAIC Bulletin expects documentation of AI systems and their controls at the decision level. Moring governs agents on that basis: each agent is registered to a use case and owner, decisions carry policy checks and evidence, and human review is recorded where the workflow requires it.
What happens if an agent exceeds its authority?
Deterministic stop conditions, step budgets, token velocity limits, and automated circuit breakers halt rogue loops instantly. Operators can immediately pause or kill any session with one click, revoking short-lived access tokens. The audit trail records exactly what happened and who stopped it.
How do we audit agent activity?
Every agent run writes a tamper-evident decision record: the agent and owner, the trigger, every prompt and model call, each retrieved document, every tool or MCP invocation with its parameters, the policy decisions taken, any human approval with the approver identity, and the resulting action. Records are cryptographically signed so auditors can reconstruct the run without asking the model what it did.