Know first. Fix once. Prove it.
48 simulated months of support at your company. OnClarity VoC finds why customers reach out, and Agentic Support fixes and resolves it.
Built from public conversations, run through the AI Return Model.
Customer counts, contact volumes and costs are estimated from public signals and industry ranges, so the result is a model of your company, not a measurement of it.
Read
We search public sources for what customers say about the company and group it into the reasons people reach out, each with its root cause.
Fix
Each reason gets one fix an agent builds: a process fix, an alert, an article, a workflow, a mini-app or a QA rule, with the month it ships.
Prove
The AI Return Model runs 48 months of support with and without the loop. Value is net support savings over three years, shown as a range.
Questions about the Fix Loop.
Public customer conversations only: review sites, app stores, forums and community threads. Every quote shown is a real customer quote, labelled with the site it came from. No private or customer data is used.
No. It is an illustrative model built from public conversations and industry ranges. It shows what changes when issues are fixed at the root cause, not a promise of results. Your numbers will differ.
Most companies take about a minute. If your company has been run before, it plays straight away.
The model needs enough public customer conversations to find the reasons people reach out. Some companies do not have that, and some categories are outside what we model publicly. Try your main company website, or book a demo and we will run it with you.
An issue counts as resolved only when it does not come back. A conversation that ends without a person is contained, not resolved.
Yes. The page link updates to your company, so anyone you send it to sees the same result.
See the Fix Loop on your real data.
A working session, not a slide deck. We agree the use cases and the success criteria, then show what the loop fixes first.
