Comparison
AI visibility tools, compared honestly — including where we lose
We build one of these, so read this knowing that. What follows is public pricing with sources and dates, plus the questions we would ask any vendor in this category — us included.
Publicly listed plans, as at 2026-08-20
| Vendor | Plan | Listed price | Listed scope | Source |
|---|---|---|---|---|
| Otterly | Lite | $29/mo | 15 prompts, daily, 4 base engines | otterly.ai/pricing |
| Otterly | Standard | $189/mo | 100 prompts, daily; API/MCP access listed | otterly.ai/pricing |
| Otterly | Premium | $489/mo | 400 prompts, daily | otterly.ai/pricing |
| Profound | Starter | $99/mo | 50 prompts / ~1,500 responses, ChatGPT tracking | tryprofound.com/pricing |
| Profound | Growth | $399/mo | 100 prompts / ~9,000 responses, 3 engines, daily | tryprofound.com/pricing |
| Scrunch | Brand Core | $250/mo | 125 prompts, 4 AI platforms | scrunch.com/pricing |
| Scrunch | Agency Core | $500/mo | Agency tier | scrunch.com/pricing |
| Peec | Brand / Agency | See vendor | 50/150/350 prompts, 3 models, daily; agencies share a credit pool | peec.ai/pricing |
| Ahrefs | Brand Radar custom prompts | from $50/mo | 2,500 checks; 1 check = prompt × platform × location; overage listed at $0.010/check | help.ahrefs.com |
| Ubersuggest | Individual–Agency | $29–99/mo | 10–20 AI prompts per project; monthly to weekly by tier | app.neilpatel.com/pricing |
| Us | Founding Agency Pilot | $499/mo | 3 client brands × 10–20 buyer questions, 3 engines, founder-reviewed report | /pricing |
Two things that table makes obvious. Prompt counts are not comparable across vendors — a "prompt" on one platform is a prompt×engine×day credit on another, so the same number can mean a 10× difference in what you actually get. And the ladder in this category runs from under $30 to enterprise, which is a category with real demand at several price points, not a niche.
Where we are the wrong choice today
- You want self-service and a dashboard. We do not have one. Several of the tools above do, at a lower price. Buy one of those.
- You want the largest prompt volume per dollar. Not us. We run a small, deliberate buyer-question set, and per prompt we are expensive.
- You want eight or more engines. We measure three.
- You want white-label, API or SSO now. None of those exist here yet.
Where we think we are the right choice
- You care which buying questions you lose, not how many prompts mention you.
- You need the citation evidence behind an answer, because you have to justify the next scope of work to a client.
- You want per-engine results and honest coverage handling rather than one blended score.
- You are willing to trade a dashboard for a reviewed report while we are early.
Questions to ask any vendor here
- Is a result ever averaged across engines?
- What happens to a failed provider call in the denominator?
- Is "mentioned" separated from "recommended"?
- Are raw answers retained, and can history be re-scored without re-paying?
- Is the question set frozen and versioned?
- Exactly which surface is measured — API, or a consumer session?
- What is the real usage limit, and what happens when it is hit?
We wrote those questions because we had to answer them ourselves. Full detail on our answers is on the tool page, including what we cannot do.
Founding pilot pricing while we validate. 14-day pilot, founder-run, cancel any time.
What we actually measure
Every result comes from the official OpenAI, Google Gemini
and Perplexity APIs with web search or grounding enabled. In our data those
surfaces are recorded as openai_api_web_search,
gemini_api_google_search and perplexity_api_sonar, and reports name
them explicitly.
That is not the same thing as a logged-in person using the ChatGPT app. These are official interfaces with web search on, but they are measurement surfaces rather than consumer sessions: no personalisation, no memory, no app-only features. Results can differ from what any individual user sees, and we do not claim the two are identical. We would rather put that on the pricing page than in the small print.