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It runs nightly. You decide twice.

Connect the helpdesk you have, or turn on the widget and help pages you’re missing. From then on it turns every customer conversation into improvements that get done: it reads everything, finds what keeps going wrong, fixes it, and measures the result. A person is needed in two places — choosing what to try, and approving anything that reaches a customer.

01

It finds what keeps going wrong

Conversations, ratings, surveys, missed reply targets and product errors, from human and AI alike, grouped into problems and counted by people — not tickets. A problem keeps its identity week to week, so a trend is real and last week’s link still works.

9 people, up from 34 said it is still broken
02

It carries out the fix

A help page rewritten, an AI answer corrected, routing changed, a ticket raised with the evidence attached, a follow-up sent to the people affected. Internal work runs on its own; anything a customer will see waits for you, word for word.

03

It tells you whether it worked

A success test written before the change, a baseline at the start, weekly readings while the window is open — then continue, revise, stop, or watch for it coming back. Most tools stop at the ticket.

18% → 11%so far, not final · 6 of 9 people confirmed · illustrative

As agentic as you let it be

Per kind of action: do it and tell me, or ask first. It starts by asking, and anything a customer will see always asks.

Everything works from Slack

Monday's choice and every approval, answered in the thread.

You can see how it knows

What each source sent, how much is graded, and how often you agree with its judgments.

Your own database

One Postgres project per workspace, redacted before the first write.

Everything it does

The QA, voice-of-customer, help-center, survey and training work a support-ops team would run — in one product, working one list. None of it is a separate tool with its own inbox.

Finding problems
AI auditLive

What your AI vendor billed as resolved against what the evidence supports, with citations and an agreement rate.

Quality on human answersLive

A graded sample of how your team answers, by topic. One number for the team; no screen ranks a person.

Targeted questions and surveysLive

Ask the people on one problem, or read your helpdesk survey answers as a source.

PeopleLive

Everyone behind a signal: what they asked, what escalated, whether they came back.

Fixing them
Help pages, AI answers, saved repliesLive

Written into your helpdesk, or into help pages hosted here if you have none — after you approve.

Training from a real problemLive

A cited module and practice built from what customers actually hit, then measured on human answers.

Help widget and assistantLive

A place for customers to ask, answered only from your approved pages, with every miss recorded.

Your own AI agentLive

Point Claude, Cursor or your own agent at a problem and its evidence. What it proposes comes back for approval.

Proving it worked
Measured resultsLive

Each fix read weekly against the weeks before it. Inconclusive when it is too early to say.

VitalsLive

Where you started against where you are, and how much of the change your fixes can defend.

HistoryLive

Problems, fixes and results on one timeline, with releases, incidents and holidays drawn against them.

Monthly reportLive

Shareable outside the team: what was found, what was fixed, what it was worth, with the arithmetic printed.

See what it connects toAsk works across all of it: a plain question about your support history, answered from your own data.