Approach
DataExos designs AI-enabled workflows so human authority remains visible, accountable, and present where the stakes require review.
Our point of view
In environments where decisions carry consequence, the answer is not to remove people from the work. It is to design the work so people stay accountable for the decisions that matter, with AI reducing friction everywhere it safely can.
DataExos builds AI-enabled workflows where human authority is explicit: where a person reviews, what they can approve or halt, and how that authority is recorded. Oversight is not a brake bolted on after deployment — it is part of how the system is designed to run.
The question is not whether a human is in the loop. It's where, with what authority, and on what record.
How oversight is structured
Not every task needs the same oversight. We classify AI use by risk, so the level of human authority fits what's at stake — routine work moves, high-consequence decisions carry mandatory review.
Tier 1
Routine, reversible, low-consequence work. AI and automation act directly, with logging for visibility but no required checkpoint before action.
Oversight: observe and sample; intervene by exception.
Tier 2
Work with real but bounded consequence. AI prepares the output; a defined review threshold determines what proceeds automatically and what is held for a person before it takes effect.
Oversight: review threshold + escalation path; a named reviewer role.
Tier 3 · highest control
Decisions about people, money, records, or regulated obligations. A human approval gate is mandatory before the action takes effect, and the decision is recorded. AI assists and accelerates; it does not act unsupervised.
Oversight: mandatory approval gate + full audit trail + sensitive-output review.
The controls
Six controls turn "a human is in the loop" from an intention into a designed, recorded property of the system.
Review thresholds
Defined points at which output pauses for a person, set by risk and by output type. What proceeds automatically and what is held is a deliberate decision, not a default.
Escalation
Clear paths for when work exceeds an agent's authority, confidence, or scope: who it goes to, on what trigger, and what happens while it waits. Designed, not improvised at the moment of failure.
Approval gates
Required human approval before a consequential action proceeds. The gate names who can approve, what they are approving, and the ability to hold, override, or halt.
Role-based permissions
Who can configure, who can approve, who can override, and who can only view. People act within defined permissions, and those permissions are part of the system's design.
Audit trails
What the AI did, what was reviewed, what was approved or overridden, when, and on whose authority — recorded so the work can be reconstructed and stood behind.
Sensitive-output review
Outputs that touch sensitive data, individuals, or regulated material are routed to human review before release — regardless of the automation tier they originated in.
The commitment behind the controls
Human-in-the-loop governance is how DataExos operationalizes its public commitment — NAI. AIFH., Not AI. AI for Humans. The commitment is that AI is deployed under human authority, observable to the people accountable for it, and bounded by review where the stakes require it.
The risk tiers, thresholds, gates, permissions, and audit trails on this page are the mechanism that makes that commitment real in operation — not a statement on a page.
Related
Tell us where AI is entering your operations and what is at stake when it acts. We'll help you set the review thresholds, escalation paths, approval gates, and audit trail that keep the right people accountable.
