How it works
When an agent gets it wrong
Agents make mistakes, and the operating model assumes it. Errors are bounded by scoped permissions and volume limits, caught by human review and evaluation, reversible because every action is recorded, and fed back as signal that improves the agent. The right question in diligence is not whether agents err, but what happens when they do.
Updated
Containment
Mistakes are bounded before they are made
The first defense is scope. An agent operates with least-privilege access and defined limits on what it may change and how much it may change in a period. A wrong decision affects the records that agent was permitted to touch, not the whole instance.
The second is the approval gate. Consequential actions do not execute until a person accepts them, so the most damaging class of error is caught before it reaches a customer or a commercial record.
Detection
Evaluation runs continuously, not at launch
RevTech evaluates agent output on an ongoing basis — quality checks on the work itself, plus the strongest available signal: how often a human edits or rejects what an agent proposed.
A rising edit rate on one agent and one action type is an early warning, and it is visible before it becomes a complaint.
- Human edit and rejection rates, tracked per agent and action type
- Output quality checks against expected structure and evidence
- Volume and rate anomalies against normal operating patterns
- Escalation when an agent cannot source what it needs to act
Recovery
Recorded means reversible
Because every action carries its actor, timestamp, evidence, and prior state, a wrong change can be identified and rolled back rather than archaeologically reconstructed.
RevTech operates the service, so remediation is our work rather than a ticket for your team, including tightening the rule, prompt, or routing that produced the error.
Frequently asked questions
See how the work gets done.
Explore how agents prepare work across your revenue teams, and how people review it, guide it and decide what happens next. Fictional data. Real product.
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