Are you actually monitoring what Fin says to your customers?
I’m curious how teams using Fin are handling this today.
Training Fin and reviewing its knowledge base is one thing but what happens after Fin actually responds to customers?
For example:
- Fin gives an incorrect answer
- Fin makes up information that isn't in your knowledge base
- Fin fails to escalate when it should
- Fin gives an answer that conflicts with your policies
- Fin closes a conversation that wasn't actually resolved
- A customer receives something potentially risky or misleading
Are you reviewing these conversations manually, relying on Intercom's analytics, or using something else?
I'm building ChatShield, a lightweight AI support compliance/quality monitoring tool for Intercom. It automatically reviews AI support conversations and flags potentially risky responses.
I'm looking for 5–10 teams currently using Fin who would be willing to try it at a very low early-user price and tell me what it catches especially teams dealing with customer support where incorrect answers can actually have consequences.
If you're interested, comment “monitoring” and I'll send you the details.
I'd genuinely also love to hear how you're solving this today, even if you don't want to try ChatShield.