What happens when the agent gets it wrong.
The answer is in the order of steps, not in a promise about model quality. The agent reads, prepares, flags doubts. A human decides.
- 01Read
The agent reads the message and pulls facts from client systems through named, read-only tools.
- 02Draft
The agent prepares a reply. Conflicting facts are marked as disputed instead of one being picked quietly.
- 03Human
An employee reads the draft, edits or rejects it, and approves. Sending starts only after approval.
- 04Log
The approval goes to the panel log together with the person who made it. aiv takes identity from authentication and records rejected attempts.
One writes, another looks for holes, a human decides.
A case from our own work in September 2026. One agent wrote code. A second one, which had not written it, was tasked with finding holes. It found five critical issues, including one where a single keystroke sent a message to a customer without confirmation. A second round found another, in the fix for the first. A human decided what to merge.
This works under two conditions. The reviewer comes from a different model family than the author, and the structure forces disagreement. Two 2026 papers confirm it: Adversarial Review and CrossAudit. The mere presence of a second agent is not enough. A single model-as-judge verdict flips in 13.6% of reruns (The Coin Flip Judge, 2026).
The engine delegates work to sub-agents and checks that the delegation actually happened, instead of accepting an invented answer. We assemble the role set at deployment.
The agent gets exactly as much access as its task requires. Not one permission more.
The scope is written down, not assumed. We agree it with your IT before the first access to data: which systems, which tools, what requires a human, where autonomy ends. Several agents in one environment get separate scopes.
One process, one prototype, your data.
We start with a bootcamp: together we pick one process and build a prototype on your data, with boundaries agreed with IT. Afterwards you decide based on how it works, not on a presentation.
Let us pick the process to show this on.
A demo on your example, with a list of boundaries to agree.