Features

Everything GetIntel measures and fixes for your AI visibility.

5 pillars scored weekly across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Per-engine probes, per-question diagnosis, done-for-you fixes.

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Foundation pillar

AI engines can crawl, read, and understand your site.

Can AI engines find your pages and parse what your product is?

Before AI can cite you, it has to be able to reach your site, render your pages, and parse what each page is about. Foundation is the technical baseline — fix it once and most of these gaps stay fixed.

What we measure

AI bot access. robots.txt rules + WAF check for ChatGPT, Claude, Perplexity, Gemini bots
Site discoverability. sitemap.xml present + valid; llms.txt declared at /llms.txt
Page understanding. Schema.org JSON-LD; meta titles + descriptions; no accidental noindex
Render quality. page readable without JS execution; server response under 1s

The fix

We generate the missing pieces for you. llms.txt drafted from your ICP. Schema.org JSON-LD generated and ready to paste into your <head>. One-hour ship.

Foundation checks · 10 total

robots.txt allows AI bots

sitemap.xml present

No accidental noindex

No llms.txt found

No Schema.org JSON-LD

Couldn't verify HTTPS cert

Score75/100

Brand pillar

AI knows who you are and recommends you to buyers.

Does AI know your product from training? Does it recommend you when asked?

Brand recognition is the second-strongest AI citation signal in 2026 research — right after content quality. AI engines act as recommenders: even great content won't get cited if AI doesn't know you as a real entity.

What we measure

Per-engine memory probe. "What is X?" with web search OFF — tests training-data knowledge per engine
Per-engine web probe. "What is X?" with web search ON — tests whether AI can find + describe you accurately
Recommendation probe. "Would you recommend X for {target buyer}?" — measures whether AI actually points buyers to you
Footprint scan. Presence on Wikipedia, Wikidata, Reddit, G2, Product Hunt, LinkedIn — the entity sources AI engines lean on

The fix

Done-for-you Brand drafts: Wikidata entry, "What is X" About-page rewrite, Schema.org entity JSON-LD. All paste-ready from your ICP + brand context.

How each AI sees you

ChatGPT

Training

Partial

Web

Knows well

Recommend

Lists as option

Claude

Training

Unknown

Web

Knows well

Recommend

Mentions you

Perplexity

Training

—

Web

Knows well

Recommend

Recommends competitors

Brand score64/100

Authority pillar

AI trusts your domain enough to surface you.

Is your domain reputable enough to land in AI's answer set?

Raw backlinks are a smaller signal for AI citations than for traditional SEO (~3% correlation in 2026 research). What matters more: are you in the 'best of {category}' listicles where AI looks for recommendations? And does your domain rating clear the trust threshold?

What we measure

Domain Rating. Ahrefs DR or DataForSEO domain rank — log-scaled so DR 42 maps fairly against DR 90+ brands
Referring domains. Total + net-new last 30 days, broken out by dofollow/nofollow
Recommendation presence. Do you appear in "best {category} tools" + "{competitor} alternatives" SERPs? AI cites these listicles.
Backlink opportunities. Editorial sites that already cover your category — ranked + scored for outreach

The fix

Outreach prospects discovered weekly with the exact pitch angle. Plus a ranked list of "earn-this-backlink" moves (guest posts, listicle inclusions) projected against your current DR.

Domain Rating · log-scaled

Your DR

+3 since signup

12 new referring domains

"Best AI SEO tools" SERPs

G2 (#3) — lists Frase, Surfer, Jasper

G2 alternatives (#5) — lists Rytr

You're in 0 of 4 "best of" SERPs

Content pillar

Your site has the answers AI looks for.

Do you have indexed, citable content for the buyer questions AI gets asked?

First 200 words of articles contain 44% of AI citation extractions. AI engines need substance to quote. Without content tuned to the specific buyer questions in your category, there's nothing for AI to cite — even with a perfect Brand + Authority score.

What we measure

Blog presence + sitemap. Article count, freshness window (last 90 days), publishing cadence trend
Buyer-question coverage. For each buyer question AI is asked, do you have a matching article? site:domain SERP check.
Citation rate. Of the buyer questions probed, how often does AI cite YOUR article vs a competitor's?
Quality signals. FAQ schema, year-in-title, article length, schema-org type coverage (Article, HowTo, FAQPage)

The fix

GetIntel drafts the article for each citation gap. Tuned to your existing brand voice. Generated body tuned for citation extraction: clear definition in first 200 words, FAQ schema, year in title.

Buyer-question coverage

"How to do X with AI"PublishedNot cited

"Best X tools 2026"GapNot cited

"X vs Y for founders"GapNot cited

"What is X?"PublishedCited

Coverage

50%

Cited

25%

Score

Rankings pillar

AI cites you over the competitors in your space.

Where do you sit in AI's actual answers — first cited or buried?

Traditional Google ranking decoupled from AI citation in 2026 — 44% of Google top-10 SaaS brands get zero ChatGPT citations. Rankings now means AI Share of Voice + citation position. Are you mentioned at all? When mentioned, are you the first option or the eighth?

What we measure

Share of voice. Your brand mentions / total brand mentions across all probed questions, per engine + aggregate
Citation rate. Probes that cite you / total probes — your "appears at all" baseline
Citation position. 1st cited = 100, 2nd-3rd = 70, 4th-7th = 40, 8th+ = 15 — being first matters 6x more than being eighth
Competitor share. Per-competitor share of voice — who AI cites instead of you, prompt by prompt

The fix

Rankings is a lagging outcome — there's no direct lever. The fix is upstream: improve Foundation, Brand, Authority, Content and Rankings climbs naturally. Our action engine surfaces fixes from the upstream pillars sorted by impact on Rankings.

Share of voice · this week

Frase

28%

Surfer SEO

21%

Jasper

15%

You

Rytr

Citation position avg4.2nd

Toolkit

The lenses + the fixes.

Two ways to see your gaps — AI Answers (per question, per engine) and Competitors (deep analysis). One way to close them — done-for-you drafts.

AI Answers lens

See exactly what each engine said for every buyer question we probed. Per-question × per-engine grid: who got cited, what was quoted, which competitors appeared in your slot. Click any question to drill into the actual AI answer.

Full per-engine answer text
Cited tools extracted + ranked
Your position when cited (1st-8th)

Competitors lens

Deep analysis of every competitor you track: pricing tiers, feature lists, messaging summary, llms.txt strategy, recent blog posts classified by category. Refreshed weekly. Diffs surface as ledger events.

Pricing + plan extraction via LLM
Messaging + positioning summary
New blog posts classified (educational, comparison, changelog…)

Done-for-you drafts

When a pillar is weak, we generate the fix — not just the recommendation. Articles tuned for citation extraction, Wikidata entries with statements, Schema.org JSON-LD, outreach emails with pitch angle. Drafts match your brand voice from your existing content.

Articles + counter-content (Content pillar)
Wikidata entries + About-page rewrites (Brand)
Outreach pitches with personalized angle (Authority)

See your Findability Score in 30 seconds.

Enter your URL. We probe ChatGPT, Claude, and Perplexity on 20 buyer questions in your space, score all 5 pillars, and show you the gap. Free, no credit card.

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