AI confidence that means something
Every approval or rejection you give an agent is counted, so Kinnow can show whether 'sure' really means sure.
LiveWhat does AI calibration loop do? See which agents have earned trust on your data and which still need a person to check every draft.
How it works
Approving an agent's task counts as right; rejecting it counts as wrong. Each is compared with how sure the agent said it was. Over the last 90 days, once there are enough examples, Kinnow checks whether that confidence matches reality, then marks the agent calibrated or not. It gives you a plain measure of how far to rely on that agent.
Work you reject is kept separate from work that failed.
Step by step
- An agent drafts something and says how sure it is. Each draft carries a confidence figure.
- You approve or reject it. In the agent queue, the draft shows its confidence beside Approve and Reject. Approving counts as "it was right". Rejecting counts as "it was wrong".
- Kinnow keeps the pair. The confidence the agent stated and your verdict are stored together, per agent, on your own data.
- Once there are enough examples, it checks. Over the last 90 days, with at least 30 examples, Kinnow compares what the agent said with how often it was right. If the average gap is within 10 percentage points, the agent counts as calibrated.
- It marks the agent calibrated or not. It gives you a plain measure of how far to rely on that agent.
- The picture moves as you keep reviewing. Old verdicts drop out after 90 days, so the answer reflects recent work.
Ask us which of your agents would be trusted and which still need checking.
What you see on screen
| On the screen | What it shows |
|---|---|
| Confidence | On every draft in the agent queue, the figure the agent stated. |
| Approve and Reject | Your verdict. Each one becomes a data point for calibration. |
| Awaiting approval | Drafts that are waiting for your decision. |
| Trust level | On the agent's own page, for example "Suggests, you decide", where a person approves every action. |
Who uses it
- Anyone who approves agent drafts: accountants, buyers, collectors. Their honest approvals and rejections are the raw material.
- Finance head or owner: decides how much to rely on an agent that has been calibrated.
- Administrator: watches which agents are earning trust.
See how your agents' confidence compares with what you approved.
Related
- Agents and human sign-off: explainable agents.
- Limits around agent outputs: guardrails.
- Numbers that show how sure they are: never a confident wrong number.
- All agents: the agents index.
Questions
What is AI calibration loop in Kinnow?
Every approval or rejection you give an agent is counted, so Kinnow can show whether 'sure' really means sure.
What changes for the business?
See which agents have earned trust on your data and which still need a person to check every draft.
Is it available today?
Yes, it is live.
How many approvals does an agent need before it counts as calibrated?
At least 30 verdicts within the last 90 days. Until then Kinnow does not give the agent a calibrated or not-calibrated mark.
Does a calibrated agent act without me?
No. Calibration only changes how its confidence is shown. A person still approves what it drafts.
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