When an answer you gave a customer stops matching your record, Kanonik tells you.
Once you’ve sent a customer an answer, you’re held to it long after the deal closes.
And the customer shouldn’t be the first to notice when it goes stale.
A saved answer stops being safe to reuse when one of these happens.
The record behind it changes.
Say an answer about admin access at Harbor Ledger, our sample company, cites version 1.2 of its access control policy. Once version 2.0 is confirmed, that answer is flagged.
Its evidence runs out.
Each piece of evidence covers a stretch of time. When that ends, the answers that cite it are flagged.
Its review date passes.
Each saved answer carries a date to look at it again. Unless someone sets one, Kanonik works it out from the records the answer rests on.
A flagged answer sits under Needs a look until someone deals with it, and every export that cites it marks it. Your AI won’t reuse it without telling you first. Kanonik’s server does all of this with fixed rules, and no model is involved.
On Audit-Ready, exceptions run out too. When one passes its end date, the requirement it covered counts as open again until someone decides what to do.
Your assistant looks at your systems whenever you ask it to.
It uses the access it already has. Ask it to check the cloud account, the code and the ticket queue, and to draft whatever has changed, a new data store or a fresh restore test report, say.
On a run Dana asked for, the assistant found September’s restore test report.
On a run Dana asked for, the assistant found September’s restore test report.
An assistant’s run beside Kanonik, with sample data from Harbor Ledger. It plays once; then it’s yours to click through.
September’s restore test report then went through the safety check and into Dana’s To decide list.
Kanonik’s weekly summary lists what’s waiting for you, and your AI can tell you what to look at first.