For local marketing agencies
AI assistants already recommend your client's competitors by name. This is how you find out - and fix it.
FoundNow samples AI assistants with the questions buyers actually type, shows which competitor domains get cited while your client is missing, and hands you a ranked fix list - then the monthly re-run verifies whether the gap actually closed. Every figure is a rate with a 95% confidence interval, never a single-point claim.
Run the free check See pricing
No sign-up and no card: 3 buyer questions, one AI assistant, and a comparison against our October 2026 benchmark of 187 cited domains.
The competitor citation gap, in one loop
Most tools stop at "monitor your AI visibility." A report nobody acts on does not move a mention rate. FoundNow closes the loop in three steps - the parts competitors skip are the middle and the end.
1 · Diagnose
An audit samples the industry's buyer-question set across the engines a given report covers - 20 to 25 buyer questions, 5 runs each - and maps which competitor domains appear where your client doesn't, wherever the sample covers them. Per-engine rates, citation sources and confidence intervals throughout.
2 · Fix
The fix armory turns the gap into copy-paste work: data-layer checklist, LocalBusiness schema, FAQ copy, review-ask templates with platform rules, and channel-readiness checks (feeds, booking endpoints, machine-readable forms).
3 · Verify
The monthly report re-runs the same questions and compares distributions month over month - so your client sees whether the intervals moved, in a PDF report carrying your own logo.
Local feed diagnostics - because assistants are becoming stores
Assistants are moving from answering questions to carrying out actions, and the direction is already visible across several AI and commerce platforms. We do not name them here or claim to track them: our measurement only covers surfaces with a public API, and we would rather leave this paragraph narrower than make a claim we cannot source. What we can tell you is whether your client is reachable in that kind of world at all - the armory checks service feed submittability, a working booking or reservation endpoint, machine-readable inquiry forms, and (for restaurants) a menu an assistant can parse. Citable is the floor; actionable is the bar.
Pricing per business location
Plans: Starter $49 · Growth $99 · Agency $249 · Scale $449 per month, covering 1, 5, 15 and 40 business locations. Extra locations can be added to Growth, Agency and Scale for $22, $18 and $13 per location per month. Annual billing is the same plans charged once for twelve months at the price of ten: Starter $490, Growth $990, Agency $2,490 and Scale $4,490 a year. One-time products: a visibility scan at $19 (credited in full toward an audit) and a full audit at $79. Reports carry your own logo on every plan.
| Plan | Monthly | Business locations | Cost per location / month |
|---|---|---|---|
| Starter | $49 | 1 | $49 |
| Growth | $99 | 5 | about $20 |
| Agency | $249 | 15 | about $17 |
| Scale | $449 | 40 | about $11 |
The per-location column is arithmetic from the plan price and is shown for comparison only. Full details on the pricing page.
Engine coverage, on the record
We sample assistants through their public APIs and state the limits plainly - including the one surface nobody can sample yet. Every report lists the exact engines and model versions behind its numbers, so you can see what was measured rather than take a claim on trust. The two competitor columns were filled from each vendor's own published pages, and each cell links to the page it came from. Check them yourself before you buy - including us.
| Capability | FoundNow | BrightLocal local-SEO suite |
Otterly AI-visibility dashboard |
Profound enterprise AI-visibility |
|---|---|---|---|---|
| AI-assistant sampling via public APIs | Yes, every plan - we call each assistant's public API and the report says so | Not stated how prompts are run source |
Not stated how prompts are run source |
Not stated how prompts are run source |
| Exact engines + model versions listed in each report | Yes - the engine and model version behind every number is in the report | Engine names published (ChatGPT, Google AI Overviews, Google AI Mode); model version strings not stated source |
Engine names published (ChatGPT, Google AI Overviews, Perplexity, MS Copilot; Claude / AI Mode / Gemini as paid add-ons); model versions not stated source |
Up to 9 answer engines listed (ChatGPT, Perplexity, Google AI Mode, Gemini, Microsoft Copilot, DeepSeek, Anthropic Claude, Google AI Overviews, Exa Search); model versions not stated source |
| Google AI Mode | Out of scope in v1 - no public API exists, and every report says so | Yes - covered today source |
Yes - paid add-on source |
Yes - on the Enterprise engine list source |
| 95% confidence intervals on every rate | Yes, standard | Not stated in their public materials source |
Not stated in their public materials source |
Not stated in their public materials source |
| Competitor citation gap by domain | Yes, wherever the audit sample covers competitor mentions | Yes - per-competitor mention rate, share of voice and average position, plus an AI sources leaderboard of cited domains source |
Yes - link citations analysis and domain ranking source |
Yes - how the brand and competitors appear in answer engines source |
| Fix list + executable armory (schema, FAQ, review asks, feed checks) | Yes | Partly - prioritised action items and a Citation Builder; no published schema / FAQ / review-ask / feed-check armory source |
Partly - recommendations and a GEO audit; the armory itself is not published source |
Partly - agents that draft and stage corrections and content; no published schema / FAQ / review-ask / feed-check armory source |
| Monthly re-run with month-over-month distribution compare | Yes, white-label | Run-to-run score comparisons shipped in Aug 2026; a distribution compare is not described source |
Daily tracking with stored history from Standard up; a distribution compare is not described source |
Daily runs with all-time history on Enterprise; a distribution compare is not described source |
Read this table honestly, in both directions. Two of the cells above are where the other vendors are ahead of us: Google AI Mode, which all three of them track and we do not, because there is no public API to sample - we would rather say that in a report than show you a number we cannot source. And "not stated in their public materials" means exactly that: they may well do it, we did not find it written down, so we are not going to claim they don't. Every competitor cell was read off the vendor's own page on the date shown, and the link in the cell is the page it came from - go and check it, and check us the same way.
Published data and industry guides
We publish our own measurement, not just claims: the AI Visibility Index is a public, reproducible citation baseline — 45 grounded AI answers to 15 local-AEO questions, 187 cited domains ranked, including our own 0/45 mention rate with its confidence interval. Industry guides with per-metro pages: dentists, HVAC companies, law firms and restaurants.
Sample reports, run in public
These three are real read-only samples, produced on October 6, 2026 by running our own pipeline against three real US businesses. Nothing is mocked and no figure is written by hand — each page lists every question asked, every answer that came back, and every source the assistant cited instead.
- austintexasdentist.com — Austin, TX (dental): 9 answers, 0 mentions. Five different practices were cited instead.
- acmeac.com — Longview, TX (HVAC): 9 answers, 0 mentions.
- austinorthodontics.com — Austin, TX (dental): 9 answers, 0 mentions.
All three scored zero. That is not a quirk of the sample — it is the thing we sell. A practice can be the best option in its own city and still appear in none of the answers, and no amount of intuition will show you that. A nine-answer sample cannot support a claim about a market; a paid plan re-runs the same measurement on a schedule and reports the distribution with a confidence interval attached.
Honest by design
AI answers vary from run to run. That is why every number we report is a distribution with a 95% confidence interval, why every sample carries the model version that produced it, why the first report states the expected 60–90 day curve in probability terms instead of promising positions, and why we name our method's limits (no public API for Google AI Mode, so it is out of scope for v1).
FoundNow launched in October 2026. We do not publish a customer count, because we do not have one yet — there is no number here worth quoting. What we publish instead is the part you can check: the method, the sample sizes, the confidence intervals, and a public benchmark that includes our own domain scoring zero out of 45. If we ever quote a figure we cannot show the working for, we will not quote it.