Before the action
Approve what commits you
Refund, goodwill gesture, contract change, payment commitment: the AI agent drafts, prepares and waits for a supervisor's sign-off before executing. Nothing irreversible goes out without approval.
Validated in production across 500 seats
AI handles the volume. Your supervisors keep the authority.
At scale, the real challenge is no longer automating — it's knowing who decides. Vocalcom governance gives your supervisors real authority over every conversation your AI agents run: observe, approve, take over, arbitrate.
The real issue
AI that's governed, not just constrained
Constraining an AI means setting limits upfront and hoping they hold. Governing it is different: every consequential decision runs through an identified authority, every action is logged, and every deviation reaches someone accountable for it. The difference doesn't show in a demo — it shows the day a regulator, a customer or your legal team asks who decided what, and why.
AI that's only constrained
?
- Rules set at launch, never revisited
- No one knows what was said across the thousands of conversations handled
- The gap surfaces when the customer complains
- No way to explain a specific decision after the fact
- The supervisor observes — they don't arbitrate
AI that's governed
100%
- Your business rules apply before the AI speaks
- Sensitive actions wait for human approval
- Supervisors watch live and take over whenever they decide to
- Every interaction logged, every decision explainable
- Authority stays with a person, not a model
The four moments
Where humans take back control
Human intervention isn't a safety net you trigger when things go wrong. These are four identified moments where a human decision is worth more than automation.
During the conversation
Settle the edge case
When the situation falls outside the defined scope, the AI agent brings in an expert instead of improvising. Your team resolves the exception, and the answer becomes knowledge available going forward.
On alert
Take back control
Rising tension, confusion, a customer insisting on speaking to someone: the supervisor is alerted and takes over the live conversation with the full history in view. The customer doesn't have to start over.
After the fact
Arbitrate and correct
Decisions made outside the usual scope are reviewed, confirmed or corrected. What's approved sets precedent across your organization; what's corrected doesn't happen again.
Your rules first
Business logic applies before the AI speaks
A well-trained conversational agent is still a probabilistic model: it produces the most likely answer, not necessarily the one your business allows. Governance reverses the order of operations.
Your rules — commitment caps, eligibility conditions, mandatory disclosures, the scope of goodwill gestures — are applied upstream of the response, not checked after the fact. Anything outside that scope doesn't execute: it goes to a human. Your terms and conditions are no longer an instruction given to the model — they become a constraint built into the system.
Three levels of view
From the big picture down to a single sentence
The executive view
Automation rate, drivers handled, volume taken back by humans, perceived quality. The question this view answers: is automation actually creating value, and where does it stop today?
The operations view
The journeys where AI hands off, the most recurring drivers, the queues under pressure, pending approvals. This is the supervisor's day-to-day control view.
The conversation view
The full play-by-play of an exchange: what the customer said, what the AI agent understood, the rule that applied, the decision made and its reason. This is the view you open in front of an auditor.
500
seats in productionAI agent gouvernance was validated under real conditions on a 500-seat operation before being rolled out to all our customers. This isn't a roadmap announcement — it's a system proven on a live production floor, with its peaks, its edge cases and its compliance constraints.
Traceability
Explaining a decision, months later
A log for every interaction
What was asked, what was understood, the rule applied, the action executed and, where relevant, who approved it. Exportable in the format your compliance team expects.
An explainable decision
For every consequential response, the system keeps the path that led to it. It's not a black box your legal team has to defend.
Rights by role
Who can observe, who can approve, who can take over a conversation, who can change a rule: scopes are defined by role, and logged too.
Frequently asked
What operations leaders ask us
How is governance different from simply constraining the AI?+–
Constraining sets limits on the model and assumes they hold. Governance adds three things: your business rules apply before the response instead of after, consequential actions wait for human approval, and every decision stays explainable long afterward. The difference shows up the day you have to account for it.
Doesn't human approval slow everything down?+–
It only applies to the actions you designate as consequential. Everything else runs without interruption. In practice, the share of conversations requiring approval shrinks as the authorized scope gets more precise — because your rulings become rules.
How many supervisors does it take to govern a fleet of AI agents?+–
Far fewer than to supervise the same volume handled by humans: one supervisor tracks several dozen conversations at once and only steps in on alert or approval request. We calibrate that ratio with you based on your real volumes.
Does this work with AI agents that aren't yours?+–
Governance is natively built into Vocalcom AI agents. For a mixed fleet, the connection runs through the third-party platform's API capabilities — that's assessed case by case, and we'll tell you plainly what's possible.
Does it work across every channel?+–
Yes. Voice, WhatsApp, chat, email: the same rules and the same rights apply, with a consolidated view per conversation regardless of the channel it started on.
How does it roll out?+–
By scope: you start with one driver or one campaign, with a deliberately wide approval boundary, then expand it as your rulings feed the rules. That's the method followed on the 500-seat rollout.
See governance on your own journeys
Bring a case where automation worries you — a goodwill gesture, a payment commitment, a sensitive complaint. We'll show you how it's governed.