Not every agent action needs approval. The important ones need the right approval.
Allow routine actions inside defined permissions, budgets and policy boundaries without unnecessary interruption.
Known actions
Low materiality
Policy compliant
Fully traceable
Facthory does not treat human review as a last-minute compliance checkbox. Decision rights are part of the agent architecture: who can approve, under which conditions, with what evidence, at what materiality and whether one or several accountable people must agree before the agent proceeds.
Define which roles can approve which classes of action, value thresholds, risks and exceptions.
Increase human involvement as materiality, uncertainty, safety impact or regulatory consequence rises.
Route questions to people with the required role, expertise, qualification or organizational responsibility.
Require dual control, quorum or separation of duties when one person should not authorize alone.
Present the recommendation, sources, assumptions, alternatives, uncertainty and expected consequences before asking for approval.
Pause, reject, redirect or terminate agent work when accountable people decide the system should not continue.
Poor human-in-the-loop design turns reviewers into manual auditors. The agent does hours of work, then hands a person an opaque conclusion and expects them to reconstruct everything before approving it. Facthory treats escalation as a prepared decision. The reviewer receives the issue, recommendation, evidence, assumptions, alternatives, confidence and consequences in one bounded package. The person can approve, reject, revise, ask for more evidence or redirect the work while the agent retains the full project state.
Agent summarizes recommendation, alternatives, assumptions, sources, risk and unresolved uncertainty.
Send the decision to the person or group with the required authority and expertise.
Humans retain explicit control over whether consequential actions proceed and under which conditions.
Store who decided, what they reviewed, why they decided and what happened next.
Facthory does not force one oversight model across every task. Organizations can allow routine work to run independently while increasing review requirements for higher-risk actions, uncertain conclusions or regulated decisions. The boundary can change by workflow, role, system, geography, data sensitivity or consequence.
Let predictable, reversible and low-impact work proceed automatically inside explicit boundaries.
Require expert review when confidence, materiality or policy conditions cross defined thresholds.
Reserve high-consequence actions for accountable people with explicit approval rights.
Human authority follows the consequence of the decision, not the interface where the agent happens to work.
Require expert approval for design changes, technical exceptions and safety-relevant recommendations.
Gate changes affecting production, maintenance, quality, customers or critical operational continuity.
Apply materiality thresholds, delegated authority and multi-person approval to financial decisions and actions.
Escalate policy exceptions, regulated decisions and ambiguous obligations to accountable control owners.
Human oversight should not mean humans approve everything. That simply recreates the bottleneck automation was supposed to remove. The stronger model is explicit delegation: agents own bounded execution, while people retain authority over the decisions whose consequence, uncertainty or policy requirements demand human judgment. As the system earns trust, autonomy can expand by evidence and policy rather than by assumption.
The goal is not human approval everywhere. It is human authority exactly where accountability requires it.
Define decision classes, consequence levels, authority boundaries and required reviewers.
Turn governance rules into executable approval and escalation policies for agents.
Send each decision to the right accountable person based on context and authority.
Approve, reject, modify or request more work from the agent with full context preserved.
Allow approved actions to continue under the exact scope and conditions authorized.
Use corrections and decision outcomes to improve future routing and autonomy policies.
Map roles and individuals to permitted decision classes, thresholds and domains.
Trigger review from risk, confidence, amount, geography, policy or other runtime context.
Prevent the same actor from initiating and independently approving restricted actions.
Record evidence, recommendation, reviewer, rationale, approval conditions and resulting execution.
Expire stale approvals when context, evidence or operating conditions may have changed.
Approve one exact action, range or plan without granting broader agent authority.
Route unresolved decisions upward or sideways to qualified owners instead of failing silently.
Use human corrections and outcomes to refine where future oversight is required.
Oversight becomes a bottleneck when every action waits for the same approval. Facthory separates routine execution from consequential decisions, allowing agents to keep working around pending checkpoints, prepare additional evidence and continue independent tasks while the right people focus only on decisions that require their authority.
Enterprise AI governance increasingly requires organizations to translate abstract responsibility into concrete runtime controls.
Human oversight is explicit
Deployers carry oversight duties
Core AI risk functions
Let agents handle the work while your organization defines exactly which decisions remain human, who owns them and what evidence is required before consequential actions proceed.
