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.
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 — each measured separately, never summed into one score
The roster is five AI engines plus one answer surface — AI Overviews — reported separately and never summed into an engine count. The five engines are measured today. The surface is 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 →