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When a buyer asks an AI assistant “what's the best tool for X”, the answer that comes back either names you or it doesn't — and there is no page two. Builder radar asks 9 web-grounded AI engines your buyers' real questions on a recurring schedule, stores every answer verbatim, and turns the results into four things you can act on:

• → Where you stand — recommended, merely named, or absent, per question and engine, versus your competitors.
• → What's wrong — answers that state false facts about you (wrong pricing, wrong category, a same-named company's details), with the engine's exact quote.
• → Why — the cited pages feeding each answer, so a loss traces to a specific listicle, thread, or review page instead of a vague “do more content.”
• → What changed — when a tracked answer moves, you get the before/after receipt: both answers verbatim, with engine and dates.

One honesty rule shapes the whole product: we show you changes, we never claim your fix caused them, and a number with no stored answer behind it does not appear anywhere.

1. 1 · Sign up and create a project. Enter your product's URL. We read your homepage to identify your category, likely competitors, and the buyer questions your prospects type into AI.
2. 2 · Review the generated buyer prompts. These are the questions we'll keep asking the engines. Edit them freely — the closer they match what your real buyers ask, the more the report is worth. Add your own; remove any that don't fit.
3. 3 · Confirm your competitors. We suggest them from your homepage and from who actually appears in AI answers; you can add or remove tracked competitors at any time.
4. 4 · Get your first sample. New projects run a live first sample right away, so you see real answers within minutes instead of waiting a day.
5. 5 · Read the Overview. Your visibility score, who AI recommends instead of you, and the most urgent wrong facts. Expect the first reading to sting — showing you a true zero is the product working, not failing.

Prefer to look before signing up? The sample report is a full illustrative walkthrough of every section below.

A project is one brand or product being tracked. A buyer promptis one question we repeatedly ask every engine on your plan — e.g. “best uptime monitoring for indie SaaS” or “is Acme worth it”. Prompts are the unit everything else hangs off: verdicts, receipts, alerts, and source maps are all per-prompt.

A good prompt set covers four intents:

• → Category shortlists — “best tools for [job you do]”, where recommendation lists form.
• → Problem questions — “how do I [problem you solve]”, where category winners get named in passing.
• → Comparisons — “[you] vs [competitor]” and “[competitor] alternatives”.
• → Verification — “is [brand] worth it”, “what does [brand] cost” — where wrong facts and identity mix-ups surface.

Changing a prompt starts its history fresh — a receipt only makes sense against the exact same question — so settle your prompt set early and resist rewording prompts to flatter your brand. The plan sets your prompt budget: 25 on Solo, 75 across 3 brands on Agency.

We track 9 answer engines — ChatGPT, Gemini, Perplexity, Claude, Grok, and search-grounded open models. Every engine is web-grounded: its answer reflects what a consumer assistant tells a buyer today, not a frozen training snapshot. We never pad the count with ungrounded model variants.

Engines are not sampled at identical rates. Flagship engines run on a daily tick; the search-grounded open models rotate through the week. Rather than rounding that up to “everything, daily”, every engine in your dashboard wears a freshness badge:

• → live — recent successful sample; the data is current.
• → stale — the engine has missed its expected window; existing data stays visible but is aging.
• → down — the engine isn't returning usable samples right now (provider outage, rate limits). Its samples stop counting toward scores rather than being quietly extrapolated.

Engines degrade occasionally — that's the reality of measuring live AI surfaces, and the badge is how we keep it honest. Answers also pass a quality filter before they count, so page junk and error screens never become verdicts.

Each project has six main surfaces, in the order you'll usually work them:

• → Overview — the brief. Visibility score with trend, engine freshness, who AI recommends instead of you, and the most urgent items from every other surface. Start here each visit.
• → Answers — the ledger. Every stored answer, verbatim and searchable, plus the receipts of answers that changed. This is the raw evidence everything else summarizes.
• → Competitors — who owns your category's answers: share of AI answers per competitor, which prompts each one wins, and per-competitor detail.
• → Sources — the causal lever. The pages AI answers cite, ranked by how many answers they feed, including the gap list: pages AI trusts that don't mention you.
• → Fix Queue — wrong facts and lost prompts turned into concrete, shippable moves with send-ready drafts (more below).
• → Activity — the changelog: answer transitions, new alerts, and shipped fixes in time order, so you can catch up after a week away.

A “More” group holds supporting views — discovered prompts worth tracking, the full AI accuracy list, demand signals, and social mentions. Their highlights also surface on the main pages, so you don't need to patrol them daily.

Every sampled answer gets one of three verdicts for your brand, and for each tracked competitor:

• → Recommended — the answer actively suggests you for the buyer's question.
• → Named — you appear, but as one option among others or in passing.
• → Absent — you don't appear at all. We show this bluntly, including a score of zero.

The visibility score averages these across real sampled runs — recommended = 1, named = 0.5, absent = 0 — scaled to 0–100. The same scale is used on every surface (dashboard, emails, client reports), so no two screens can disagree.

Two reading rules save a lot of false alarms: a single run is a data point, never a trend — AI answers vary run to run, so judge weeks, not screenshots. And a low first score is normal; most brands discover they're absent from questions they assumed they owned. That reading is the starting line, not a verdict on your product.

A receipt is the before/after record of a tracked answer that changed: the same prompt, the same engine, both answers verbatim, with dates. Improvements and declines both get receipts — the point is a record you can act on (and hand to a client), not a highlight reel.

Change alertsfire on real transitions only: you or a competitor entering or leaving an answer, or a new source starting to feed it. One-off wording wobbles don't alert — answers are non-deterministic, and alerting on noise would train you to ignore the alerts that matter. Each transition alerts once. Where evidence is too thin to call, the product says inconclusive instead of guessing.

And the rule that runs through everything: when an answer changes after you shipped a fix, the receipt says the answer changed. It never says your fix caused it — nobody can prove that, so we don't sell it.

An accuracy alertfires when an engine states something about you that contradicts your own published facts: wrong pricing, a feature you don't have, the wrong category — or the quiet killer, entity confusion, where the engine describes a similarly-named company under your name.

Each alert shows the incorrect claim, the engine's verbatim quote, the true fact, severity, how many times it's been seen, and when it was last seen. Alerts carry a confidence label (low → medium → high → verified); high-severity claims are re-checked across independent model families before they count, so you're not chasing a hallucination of a hallucination.

From any alert you can jump to the Fix Queue to get a correction drafted against the source most likely teaching the engines the wrong fact.

The Fix Queue turns each wrong fact and lost prompt into one concrete move. For a lost prompt: the specific cited source feeding the competitor's win, how much leverage you realistically have over it, and a send-ready draft — a pitch to the listicle's editor, a transparent contribution to the thread, a review profile to complete, or a comparison page to publish yourself. For a wrong fact: a polite, sourced correction request plus a clarification for a page you own.

• → Drafts contain bracketed placeholders for facts only you know. Fill them honestly — the drafts never fabricate numbers, and neither should you.
• → Nothing sends automatically. You copy the draft out, review it, and ship it yourself — it's your name on the outreach.
• → Mark a move shipped and the queue keeps re-sampling that prompt, reporting whether the answer changed — up or down.

Set the horizon accordingly: answers move over weeks to months as engines re-crawl, and some never move. The queue is designed for that reality — a short list of the next things worth shipping, not a slot machine.

• → Weekly analyst email — only sent when there's something meaningful: what changed, why it matters, the sources behind it, and the top next actions. A quiet week means no email, not a padded one.
• → Movement alerts — answer transitions as they're confirmed. Agency plans can route these to Slack as well as email.
• → Monthly client report (Agency) — a white-label summary suitable for forwarding straight to a client.

Every email has a working unsubscribe link, and notification preferences live in Settings.

Free is a one-time snapshot: your buyer questions sampled once on Gemini — your score, who AI recommends instead, and a read-only preview of wrong facts and lost answers. No card, no ongoing tracking.

Solo ($49/mo) is continuous tracking for one brand: all 9 engines, 25 buyer prompts, the full receipts ledger, change and accuracy alerts, the Fix Queue, the source map, and the weekly email.

Agency ($129/mo) is everything in Solo for 3 brands and 75 prompts, plus white-label reports, CSV export, API keys, webhooks, an MCP server, 3 team seats, Slack alerts, per-competitor battlecards, and 60-day history.

Lifetime plans (when offered) are scan-based: you trigger checks on demand from a monthly pool, plus an automatic weekly heartbeat that keeps receipts and change alerts current. Full details on the pricing section; all paid plans carry a 7-day money-back guarantee per the terms.

• → White-label client reports — your branding on a shareable, printable report where every number traces to a stored verbatim answer. Built to survive the client asking “how do you know?”
• → CSV export — the answer ledger as data, for your own reporting stack.
• → API keys & webhooks — pull findings into your systems, or get pushed when answers change. Keys are managed in Settings; treat them like passwords and rotate any key you suspect exposed.
• → MCP server — connect Builder radar to AI assistants that support the Model Context Protocol, so you can query your own visibility data in natural language.
• → Team seats — invite up to 3 teammates; access is per-account, so never share logins.

If you're building a monthly reporting practice on top of this, the playbook in Reporting AI Visibility to Clients Without Overclaiming is the recommended structure.

• → What we store: the AI answers we sample (they're what you're paying to audit), your project settings, prompts and competitors, and the facts you publish that we check answers against.
• → What we don't do: no tracking scripts on your website, no access to your analytics, no crawling behind your logins. Everything we measure is what a public AI assistant says.
• → Deleting a project removes its tracked data; account deletion and data-export rights are covered in the privacy policy.

• “My score is zero — is the tool broken?”
  Almost always the tool is working and the zero is real. Open the Answers ledger and read the stored answers for your prompts — if your brand isn't in them, that's the finding. Absence is exactly the information the first report exists to deliver.
• “I asked ChatGPT myself and got a different answer.”
  Expected. Answers vary run to run, by account history, and by whether browsing was on. That's why we sample repeatedly and judge transitions over weeks — one chat (yours or ours) is a data point, not the truth.
• “An engine shows stale or down.”
  Engines degrade occasionally — provider outages and rate limits are part of measuring live AI surfaces. Nothing is required from you; the badge exists so aging data can't masquerade as fresh. If an engine stays down for days, we're on it.
• “I shipped a fix — when will the answer change?”
  Weeks to months, sometimes never — engines re-crawl on their own schedule. Keep the move marked shipped and let the re-sampling watch it. Beware anyone promising faster.
• “Can I change my prompts?”
  Yes, anytime — but a changed prompt starts its history fresh, since a before/after receipt is only meaningful against the identical question.
• Something else?
  Email support@builderradar.pro — a human reads it.