ResolveCheck: trust score for AI support replies

Tell a real resolution from one that only sounds finished, so support teams stop paying twice

Problem

A SaaS operator shared that a bot gave a beautifully written reply that was wrong on the one detail that mattered; a human had to reopen the ticket and redo the whole thing. Deflection metrics went up while the team's workload stayed flat, because the reply only sounded finished. Everyone running an AI support layer is asking the same question: how do you tell a real resolution from a fake one?

Solution

A lightweight ticket audit tool: connects to an existing helpdesk or imports exports, cross-checks every AI reply marked as resolved with a second model or human-defined rules, produces a confidence score, and highlights tickets that may have been closed incorrectly; gives support managers a fake-resolution trend chart.

Users

Small and mid-size SaaS support teams that already layer AI on their helpdesk, support outsourcing firms, and customer success leads.

MVP

CSV import or read-only Zendesk/Intercom integration; rechecks and scores closed tickets; outputs a high-risk ticket list; weekly email report on fake-resolution trends; free tier of 200 ticket checks per month.

Revenue

Tiered subscription based on ticket volume starting at $29/month; private deployment and custom review rules for larger teams.

Why now

AI support is already widespread, but teams are only now realizing that 'sounding resolved' pollutes metrics and creates duplicate work; this niche doesn't require replacing the helpdesk, so an indie developer can enter as a plug-in.