Solutions
Updated August 3, 2026
Run AI-search visibility for every client, from one place you can defend
If you operate marketing for multiple clients, the AI-search question is already on your desk. A client saw a competitor recommended in ChatGPT and wants answers. Another wants “AI SEO” on next quarter’s scope and you need to price it. And the tooling reality is grim: point tools for citation tracking, another for logs, another for audits, spreadsheets holding it together, and a stack bill of $500 to $2,000 a month that still cannot answer “did the work move the number?”
Answerworthy was designed multi-client first, by an operator who ran this exact work across client engagements before building the platform.
Run a free scan on a client domain
The problems this actually solves
You cannot pitch or report on what you cannot measure credibly. Clients are skeptical of AI visibility claims, and they should be: most of what circulates is screenshots. Answerworthy’s measurement is statistical and evidence-backed, and every claim in every report is tagged OBSERVED (with a link to the stored evidence) or INFERRED (labeled interpretation). When a client, or their CFO, pushes back on a number, you click through to the raw engine responses that produced it. That is what retains accounts.
Manual testing does not scale past one client. Running fifty questions across four AI engines every week is two hundred engine calls per brand per week. Answerworthy runs panels on schedule per brand, extracts mentions, citations, sentiment, and factuality automatically, and alerts you only on statistically real movement, so your team reads findings instead of running prompts.
Every client is a separate world. Each brand lives in an isolated workspace with role-based access, including client-safe read-only seats and expiring share links. Your client sees their data, only theirs, in a clean read-only view.
Reporting eats the margin. PDF reports render per brand, ready to carry your agency’s branding: a baseline report for kickoff and an executive monthly that leads with the four KPIs and what changed. The methodology appendix ships in every report, which means the rigor is not just yours internally, it is visible to the client paying for it.
The four layers, sold as a service
Each measurement layer maps to work you can scope and bill:
| Layer | The client deliverable |
|---|---|
| What AI says | Baseline visibility audit, competitor share of voice, quarterly trend reporting |
| What AI bots do | Crawler analytics with verified bot data; the crawl-to-citation gap as a prioritized opportunity list |
| What’s broken | The 91-check site audit with fix recipes; generated schema, llms.txt, and content briefs your team ships |
| How it connects | Search Console and GA4 joined in, so the story ends in traffic numbers |
The unified fix list turns all of it into a ranked backlog per client, and fix verification (re-checked, never self-reported) turns your retainer into a loop with receipts: here is what we found, here is what we shipped, here is the re-measurement showing it worked.
Pitching with it
Prospecting workspaces let you run a real scan and a real baseline for a prospect before they sign, then convert the workspace to a client without rebuilding anything. The free scan is a useful foot in the door: send a prospect their own scan results and let the evidence open the conversation.
Honest notes for operators
We are early. We have no case-study wall to show you yet, and we will not invent one. What we have is a measurement methodology you can read in full and hold us to, a platform built multi-client from the schema up, and seat pricing (Agency at $78 per brand seat/mo with a 5-seat minimum, so ten client brands run at $780/mo) designed to be a fraction of the stack it replaces. Kick the tires on your own agency’s domain first; that is what the scan is for.