FIN able to detect loops/ count turns/ conversation duration | Community
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FIN able to detect loops/ count turns/ conversation duration

Related products:Fin & AI
  • July 22, 2026
  • 0 replies
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What has been tried: We attempted to address this by implementing and refining a configurable looping behavioural instruction rule, including expanding the frustration signal vocabulary and broadening the trigger criteria. Testing confirmed the rule fires reliably for verbatim-repetition loops. For progressive loops — where the customer advances the conversation rather than repeating it — the rule does not fire. This is a platform-level constraint, not a configuration gap: cross-turn state tracking is not available within the current behavioural instruction layer.

We are requesting a conversation-state-aware loop detection mechanism built into Fin's core runtime, with the following properties:

1. Turn counting with topic continuity tracking Fin should track, across turns, whether the customer's underlying issue has changed or whether they are persisting with the same root problem. A customer who addresses the same issue across 3+ turns — even from different angles — should be flagged as looping, not just customers who repeat the same sentence. Sometimes looping shows differently accross each conversation, it may appear as progressive instead of stagnant. 

2. Frustration signal accumulation Rather than a single-turn evaluation ("does this message indicate frustration?"), Fin should accumulate frustration signals across the conversation. A neutral message following two rejected or corrected responses should be scored differently than the same message at the start of a conversation.

3. Conversation re-open recognition If a customer re-opens a conversation (within, e.g., 24 hours) after it was closed as assumed resolved, Fin should treat this as a strong signal that the prior session did not resolve the issue and apply a lower escalation threshold in the re-opened session.

4. Time awareness Fin should be able to tell how long a customer is involved in the conversation with FIN and make a call depending on the time spent chatting to offer human assistance or not

 

All these should be confiurable on workspace level and useable in guidance to customise FIN messaging to customer.