A chatbot that makes the same mistake every week isn't learning - it's just wrong on a schedule. Wonderchat is built around a correction loop: when the agent gets something wrong, you fix it once, and that fix feeds back into how the agent retrieves and answers, so the mistake doesn't return.
Spot a weak or incorrect answer, correct it, and the agent incorporates that correction going forward. You're not rewriting source documents and hoping the change propagates, and you're not filing a bug and waiting - the correction takes effect and the next person asking that question gets the better answer. Over time, the agent's answers converge on what your team actually considers correct, because your team has been steering them.
This is what makes the agent get better in production instead of drifting. Every correction is a small, permanent improvement, and they compound: the more real questions the agent handles, the sharper it gets at the ones that matter to your customers.
It sits alongside grounding and citation as the third pillar of accuracy - answer from your content, show the source, and improve from every correction. It's part of a SOC 2 Type II certified, GDPR-compliant platform. Teach it once, and it stays taught.
FAQ
Can I correct the AI's answers and have it learn?
Yes. Fix a weak answer once and the correction feeds back into how the agent retrieves and answers, so the same mistake doesn't return.
Do I have to rewrite my source documents to fix an answer?
Does the agent get better over time?
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