Honest comparisons · updated 2026-07-24
Compare AEO / GEO providers
By Logan Adams, Founder Reviewed & updated Every third-party fact is quoted from the vendor's own public materials and dated on the detailed pages. How we measure.
A hub for choosing an AI-search-optimization provider — tools you drive, and done-for-you services. Each comparison starts with why people pick the alternative, names who should stay with it, and keeps our own bias visible. Every comparative claim links to a dated source.
Disclosure: Clear Cited runs these comparisons. Our own entry is written in the first person so the bias is visible, and every entry — including ours — lists real drawbacks. Verify anything that matters to your decision directly with each vendor.
Pick your comparison
Start with the one closest to your decision. Each is a full, sourced fit-map — not a ranking.
Best AEO for developer tools
The flagship provider comparison for dev-tools teams — tools and done-for-you services on the same criteria, with our own drawbacks in view.
Best AEO for B2B SaaS
The same honest fit-map framed for B2B SaaS buyers — who to pick when a competitor is the better call.
Profound alternatives
Weighing a specific dashboard? A sourced alternatives map — including when Profound is the right pick and you should stay.
Not sure what you need?
Answer a few questions and get a neutral recommendation — a tool, a service, or a specific competitor.
Where we win — and where a competitor is the better call
A comparison that never sends you elsewhere isn't a comparison, it's an ad. Here's the honest split. Every "we win" cell is reproducible; every "pick them instead" cell names who and why.
| If you want… | Best pick | Why |
|---|---|---|
| a published measurement method — run-counts and confidence intervals, not just a score | Clear Cited | we publish the method and the variance; almost no provider in this category publishes either. Method → |
| per-piece citation receipts (which engine cited which page, and when) | Clear Cited | every piece we publish is attributed to the AI citations it earns. How → |
| it measured and fixed for you at a fixed public price, no calls | Clear Cited | done-for-you for dev-tools & B2B SaaS; every price on /pricing/. |
| the deepest enterprise dataset and the most engines | Profound | honestly, stay — nothing here beats its coverage at the top end. Details → |
| to try AI-visibility tracking free before paying | AthenaHQ | a genuinely free tier across several engines. Details → |
| the lowest entry price on a self-serve dashboard | Otterly | low monthly entry with a no-card trial. Details → |
| a generalist for e-commerce or consumer brands | A generalist agency | we focus on DevOps, developer tools and B2B SaaS — outside that, pick a generalist. |
The "pick them instead" rows are why we're not the right call for everyone — a tool you drive, enterprise depth, a free tier, the lowest price, or a non-technical vertical each point elsewhere. Our full drawbacks live on each detailed page.
Get a free teardown See our pricing
The transparency wedge
A method you can reproduce
pre-registered prompt sets with published hashes, run counts and a confidence interval on every figure, and null results published on the same terms as positive ones - as standing practice, not a one-off study
at least 10 runs per engine (12 by default), spent adaptively — more on high-variance engines, fewer on stable ones, never below a 5-run floor Every presence figure carries a Wilson 95% confidence interval. Share of model carries a percentile bootstrap 95% confidence interval in the paid audit, and a Wilson 95% confidence interval in the public AI Visibility Index — the method matched to the metric and named per product, both computed from the actual runs.
Confidence intervals are reported honestly wide and named per product: presence uses a Wilson interval in both products; share-of-model uses a percentile bootstrap in the paid audit and a Wilson interval in the public Index, whose pooled denominator is clustered - so those Index intervals are narrower than a cluster-corrected estimate would give, and we say so. We never narrow a CI to look more certain than the data is.
We publish our run counts, our uncertainty and our pre-registered prompt sets. Across the 8 providers we checked on 2026-08-02: run counts 4 of 8 verified; 4 not verified; uncertainty on published figures 2 of 8 verified; 6 not verified; the prompt set published with the results 0 of 8 verified; 8 not verified. The full comparison, with each vendor’s own wording →
That is the wedge: a number you can re-run and get back. See the full method →
Hold us to it, and hold the others to it too — the 12 questions to ask anyone selling AI visibility, each one answered here with a link.
Most AEO optimizes only the slice of citations you own. Here's the whole map — all four tiers AI cites from, and how much of it we actually work.
Clear Cited works all four tiers
Coverage 100% · Control ~86% · Influence ~94% · Earned (best-effort)
Most AEO optimizes the ~44% you own. Clear Cited works all four tiers.
Control ~86% · influence ~94% · the last ~6% earned — worked, not guaranteed.
Source: Yext (6.8M citations), 2025-10 — a third-party citation-tier mix, not measured by our AI Visibility Index (which tracks share-of-model); illustrative of the tier split until we publish our own measured citation-source mix
Coverage is the scope of what we work — never a control or ranking guarantee. · See the full Citation Control Map →
Why Clear Cited
The five levers behind share of model
We get you recommended across the 5 AI engines — ChatGPT, Perplexity, Claude, Gemini, and Grok — plus Google's AI surfaces (AI Overviews & AI Mode), measured separately — and here is the honest system beneath it: what you are actually paying for, and the real limit on each.
Every engine and surface your buyers actually use
the AI engines your buyers use, plus Google's AI surfaces and Bing's Copilot answers — each measured separately, never summed into one score
The roster is five AI engines plus two answer surfaces — AI Overviews and Microsoft Copilot — reported separately and never summed into an engine count. The five engines are measured today. Both surfaces are positioned, not measured: an engine is one foundation-model family we query directly, a surface is a product that renders an answer, and a surface never becomes an engine by being added up. Outside the labelled separate-surface panel we name the Google surface plainly as AI Overviews, because naming it beside the engines would read as an engine claim.
A method you can reproduce
pre-registered prompt sets with published hashes, run counts and a confidence interval on every figure, and null results published on the same terms as positive ones - as standing practice, not a one-off study
Confidence intervals are reported honestly wide and named per product: presence uses a Wilson interval in both products; share-of-model uses a percentile bootstrap in the paid audit and a Wilson interval in the public Index, whose pooled denominator is clustered - so those Index intervals are narrower than a cluster-corrected estimate would give, and we say so. We never narrow a CI to look more certain than the data is.
All four tiers AI cites from
we work all four tiers AI cites from — not just the fraction of your presence you directly own
This is SCOPE — the tiers we work, not an outcome we promise. The per-tier percentages are illustrative (Yext-sourced) and the earned tier (news & forums) is best-effort, never guaranteed.
Almost none of your time
your time required is almost none — sign-off graduates to become yours by default once we've earned a track record, with continued sampling
A human approves every client deliverable until a clean track record is earned; graduation is opt-in, default-off, and reversible — client-facing and published content never reaches unattended auto (AI speed, human-approved).
A system that compounds
the system learns which of your pages get cited and compounds that signal every cycle
Honest-empty until measured — attribution shows the real citations a piece earns, with the engine, prompt and date, only once they are actually earned; no projected compounding curve.
The system compounds — see how it learns which of your pages get cited → · the four tiers of citations we work →