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Enterprise Plan

Enterprise AEO and GEO, built for cybersecurity portfolios.

Most AI visibility tools stop at the scoreboard. GrackerAI Enterprise monitors 1,000+ real buyer prompts hourly across all 10 engines using cybersecurity-tuned models, tracks every product in your portfolio separately, diagnoses exactly why each miss happened, and turns every finding into assigned work with an owner and a due date. Measurement, diagnosis, and execution in one system, on single-tenant infrastructure.

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Our Customers
SSOJet
NHI
MojoAuth
Gopher
LogicBalls
CloudDefense
Mailazy
Procyon
Voksha
Squirrelvpn
Problem

Why Enterprise AI Visibility Programs Stall

The AI search gap is real, but the tools meant to close it are built for everyone, which means they're tuned for no one.

They guess your prompts

Most platforms invent a short list of prompts they think buyers use. If the prompts are wrong, every metric built on them is wrong too, and a few dozen prompts cannot cover how security buyers actually research.

They use general-purpose models

A generic model does not know that SOC 2 SIEM, FedRAMP authorized, and agentless CSPM are buying signals, so it misreads what a citation is actually worth.

They treat your brand as one product

Security companies almost always sell a portfolio: endpoint, identity, cloud, network. Tools that roll everything into one score hide which product is winning in AI search and which is invisible.

They report the gap and stop there

Knowing you are not cited is the easy half. Without knowing which page failed, how badly it missed, and which competitor page the engines actually pulled instead, your team is guessing at a target it has never been allowed to see.

They give you findings, not work

A hundred red cells and no owners is not a program. Every finding that has to be retyped into a separate tracker loses its context on the way, and most of them never make the trip at all.

They check once a day

AI answers shift within hours. Daily snapshots miss the volatility that decides whether you are cited on a Tuesday afternoon.

They share infrastructure

For security-conscious organizations, multi-tenant data handling is a procurement blocker before the conversation even starts.

They hand you a dashboard and leave

No strategist, no roadmap, no one accountable for the outcome.

Enterprise fixes the inputs first: the right prompts at scale, models that speak security, per-product coverage, and every prompt mapped to a page. Then it explains every miss. Then it turns each explanation into work someone owns. That last part is where programs either compound or quietly die.

Know

Measure, Understand, Diagnose

Cybersecurity-tuned analysis models

Models tuned on cybersecurity language, buyer intent, and competitive context. They understand compliance terminology, product categories, and threat-model framing, so the platform knows when an AI mention is a genuine recommendation versus a passing reference, and scores it accordingly.

1,000+ real buyer prompts, monitored hourly

Enterprise tracks 1,000+ prompts across all 10 engines, checked hourly rather than daily. Prompts come from a curated cybersecurity library mapped to real buyer journeys, from data-provider partnerships that capture what buyers actually type, and from prompt mining that pulls the questions people ask in People Also Ask and in the forums and communities where security practitioners argue. Every mined question carries an estimated search volume, so the roadmap gets prioritized by demand rather than by opinion.

Prompt Topics and Share of Voice by Topic

Group prompts into the subjects your buyers think in: zero trust, SOC 2, FedRAMP, migration, pricing, each product category. The Share of Voice by Topic matrix then shows how you stack up against every competitor per subject. At portfolio scale this is the difference between knowing your score moved and knowing that a rival now owns every compliance question in your identity category.

Per-product tracking, with a workspace roll-up

Every product line is monitored as its own entity, with its own prompt library, its own competitive set, and its own dashboard. Workspace View then rolls the portfolio into one read: visibility, presence rate, sentiment and citations across everything, plus the movers calling out exactly which product gained and which lost ground this week. Product marketers get their own number. Leadership gets one view. Nothing is blended at the measurement layer.

Technical AEO Audit across your full sitemap

Every page is crawled and scored on two dimensions. AEO Health covers off-page authority, content structure, evidence, retrievability including AI-crawler access and page speed, freshness, and schema. Technical Health covers Lighthouse performance, SEO, best practices, accessibility, and Core Web Vitals. Every problem surfaces as a graded issue with a severity and a fix, with a brand-wide health view showing average scores and how many pages remain unaudited, ranked worst first. On Enterprise this runs across up to 100K pages.

Visibility Diagnosis on any prompt you are losing

This is the part most platforms do not have. Point the diagnosis agent at any prompt where a competitor wins. It searches your own site for the page that should be answering it, scores how well that page actually matches the buyer's question, and pulls the competitor pages engines cited for that prompt over the last 30 days. Then it branches. If no strong page exists, you get a content brief with the title, angle, outline, and the specific claims that earn citations in your category. If a page exists but keeps losing, you get a gap report instead: prioritized fixes, missing subtopics, structure and evidence gaps, and a freshness comparison against the page that beat you.

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Competitor intelligence, including the rivals you have not named yet

Head-to-head share of voice against your tracked competitors, plus Discovered, which surfaces new competitors entering AI responses in your category and how often they appear. In security, where a well-funded entrant can go from unknown to shortlisted in two quarters, that early warning matters more than the incumbent comparison.

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Citation intelligence: who the engines trust, and when that changes

Top Citing Domains shows which sources the engines lean on when answering prompts in your category. New Citation Sources shows what has recently started being cited. Lost Citation Sources shows what stopped, which is usually the first visible sign that visibility is slipping. A dedicated Reddit view rolls citations up per subreddit across every tracked prompt, so you can see exactly which communities the engines are pulling from in your space.

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Position Distribution and alerting

Being mentioned is not the same as being mentioned first. Position Distribution shows where in an AI response your brand appears, from Hero in the first third through to Tail in the last, because earlier placement carries more weight with the buyer reading it. Alerts fire automatically on visibility, sentiment, and competitor changes worth a closer look, and each one can be acknowledged, dismissed, or resolved, so the alert stream stays a queue rather than becoming noise.

Act

Decide, Then Ship

Recommendation Engine, split On Page and Off Page

One impact-ranked list of what to do next, in two tabs. On Page surfaces your own weak spots: prompts with low visibility, prompts worth optimizing, and pages with low AEO or technical scores, fed by the audit and by diagnosis. Off Page surfaces external opportunity: domains cited on prompts where you are absent, and rivals appearing alongside you that you are not yet tracking. Each card states the problem, the action, and links straight to where to act. Fix what is yours, or go earn citations elsewhere, ranked honestly against each other.

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Tasks, so findings become owned work

Nearly every screen has an Add Task button. Citations, prompts, responses, alerts, content gaps, discovered competitors, diagnosis reports, page audits. Each task arrives pre-filled with its source context and a what-to-do checklist, and supports assignees, priority, status, and due dates, with overdue flags and automatic de-duplication so the same finding never spawns two tickets. This is the layer that makes a thousand-prompt program governable by a real marketing team.

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Content Engine, for new pages and for the ones you already own

Articles structured for how AI engines extract and cite, not for how Google ranks. Comparison pages, category authority content, and compliance coverage across SOC 2, HIPAA, FedRAMP and ISO 27001, aimed at the specific prompt-to-page gaps the audit and diagnosis found. When a page you already own is losing the citation, the engine analyzes and restructures that page instead of generating a competing one, so you keep the authority the URL already earned.

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Brand Voice, enforced

Save your voice once as a structured profile: tone, personality, value proposition, positioning, key messages, and explicit always and never rules. Every generated article writes inside that profile automatically, and the never list is treated as a hard constraint rather than a preference. In a category where the gap between reduces risk and eliminates risk is a claim you have to defend, that distinction is the reason content automation clears legal review.

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Connect

Wire It Into How You Already Work

GrackerAI MCP

Expose your visibility data to any Model Context Protocol client, including Claude, over a read-only connection scoped to the brands you authorize. Your analysts ask questions in natural language from the assistant they already have open, without a seat, a login, or an export.

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Publishing and search data

Publish generated and rewritten articles straight to WordPress with the featured image, category, and draft-or-publish control set, or to any other CMS and headless CMS in the stack. Google Search Console and Bing Webmaster Tools connect inbound, folding the queries already reaching your site into the monitored prompt set.

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Enterprise platform controls

Single-tenant deployment on isolated infrastructure. SSO and SAML. API access. Approval workflows before anything publishes. White-label reporting.

How It Works

The 90-Day Program

Weeks 1-2

Discovery and real-prompt audit

We pull real buyer prompts from our data partners for your category, load your cybersecurity prompt library, mine additional questions from People Also Ask and practitioner communities, and stand up monitoring for 1,000+ prompts across all 10 engines, broken out per product. Prompts are grouped into topics that match how your buyers segment the category.

Weeks 3-4

Diagnosis and prompt-to-page mapping

The full Technical AEO Audit runs across your sitemap, grading every page on AEO Health and Technical Health. Visibility Diagnosis runs on your highest-value missed prompts, returning briefs where no page exists and gap reports where one does. Every finding lands in the Recommendation Engine, ranked, and converts into assigned Tasks with owners and dates. Your strategist delivers the prioritized roadmap.

Weeks 5-8

Content launch and monitoring

Content ships against the mapped gaps, in your saved brand voice, published straight into your CMS. Existing pages that were losing citations get rewritten rather than replaced. Hourly monitoring tracks first citation movement, and alerts flag the first prompts to turn.

Weeks 9-12

Optimize and scale

Optimization cycles against live data. Share of voice by topic and by product, competitor movement including newly discovered entrants, citation source gains and losses, position distribution shifts, and pipeline attribution, reported back through your strategist and reviewed quarterly.

Full Feature Set

What's Included in Enterprise

Monitoring and Intelligence

  • Hourly AI visibility monitoring across all 10 engines
  • 1,000+ prompts monitored, per product
  • Cybersecurity-tuned analysis models for accurate citation scoring
  • Cybersecurity prompt library, pre-mapped to buyer journeys
  • Real buyer prompts sourced through data-provider partnerships
  • Prompt mining from People Also Ask and practitioner communities, with volume estimates
  • Prompt Topics with Share of Voice by Topic against every competitor
  • Page-level monitoring up to 100K pages, each mapped to target prompts
  • Technical AEO Audit scoring AEO Health and Technical Health per page
  • Visibility Diagnosis on any missed prompt, returning briefs or gap reports
  • Competitor share of voice, plus Discovered for new entrants
  • Top Citing Domains, New and Lost Citation Sources, Reddit citation view
  • Position Distribution from Hero to Tail
  • Alerts with acknowledge, dismiss and resolve states

Optimization and Workflow

  • Recommendation Engine with On Page and Off Page tabs
  • Tasks with assignees, priority, due dates, overdue flags and de-duplication
  • Multi-product tracking with Workspace View portfolio roll-up
  • Per-product movers showing weekly gains and losses

Content

  • Articles structured for AI citation across cybersecurity categories
  • Compliance coverage: SOC 2, HIPAA, FedRAMP, ISO 27001
  • Comparison and category articles aimed at mapped gaps
  • Rewrites of existing pages that are losing citations
  • Brand Voice profile with enforced never rules
  • Automated internal linking and schema markup

Integrations and Platform

  • Google Search Console and Bing Webmaster Tools
  • GrackerAI MCP, read-only, scoped to authorized brands
  • Single-tenant deployment on isolated infrastructure
  • SSO and SAML, API access
  • Approval workflows before publish
  • White-label reporting

Support

  • Dedicated account manager
  • 4-hour support response SLA
  • Quarterly business reviews
  • Custom onboarding and training
Objection Handling

Generic AI Visibility Tools vs. GrackerAI Enterprise

Generic AI visibility toolsGrackerAI Enterprise
PromptsSynthetic, guessed, a few dozen, brand-heavy1,000+ real buyer prompts across brand, competitor, category, vertical and problem-aware intent
ModelsGeneral-purposeCybersecurity-tuned analysis models
ProductsOne blended brand scoreEvery product tracked separately, rolled up in Workspace View
Analysis unitOne flat prompt listTopics, with share of voice per subject
Page coverageNone, or homepage onlyUp to 100K pages, graded on AEO and technical health
When you are not citedA red cellA brief or a gap report, with the competitor pages engines actually cited
What happens nextYou export a reportThe finding becomes an assigned task with context attached
CompetitorsThe list you typed at setupPlus newly discovered entrants surfaced automatically
MonitoringOnce dailyEvery hour
DeploymentMulti-tenant, sharedSingle-tenant, isolated
SupportTicket queueDedicated account manager, 4-hour SLA
Starting pointBlank dashboard, days of researchPre-built cybersecurity prompt library across SIEM, IAM, CSPM, EDR and compliance
Proof

Transform AI Visibility and ROI

25%+

Average AI visibility increase in 90 days

4.4×

Higher conversion rate from AI-referred traffic

80%

Content cost reduction vs in-house production

4-8 wks

Time to first AI engine citations

Diagnosis, not just detection Every miss comes with the reason and the page that beat you.
Findings become work One click from any screen to an owned, dated task.
Portfolio native Every product measured separately, read together.
Single-tenant Built to clear enterprise security review.
"
AI-optimized content positioned us as experts in our niche. The results have been game changing.
+73% AI Visibility
+48% Business Impact
Edward Zhou
Edward Zhou Co-founder and CEO, Gopher Security

Frequently Asked Questions

Questions enterprise security teams ask about GrackerAI

Hourly monitoring of 1,000+ real buyer prompts across all 10 AI engines, cybersecurity-tuned analysis models, prompt topics with share of voice per subject, page-level auditing up to 100K pages graded on AEO and technical health, Visibility Diagnosis on any missed prompt, per-product tracking with a workspace roll-up, the Recommendation Engine and Tasks workflow, the Content Engine with enforced brand voice, single-tenant deployment, SSO and SAML, API and MCP access, and a dedicated account manager with a 4-hour support SLA.

Monitoring tells you that you are not cited. Enterprise tells you why. Visibility Diagnosis searches your own site for the page that should have won the prompt, scores how badly it missed, and shows the competitor pages the engines actually cited over the last 30 days. Then it produces either a content brief or a prioritized fix list, and turns it into an assigned task. Detection is the commodity. Diagnosis and execution are the product.

Custom, based on prompt volume, page-level coverage, and the number of products in your portfolio. Contact sales for a quote tailored to your program.

All 10: ChatGPT, Perplexity, Google AI Mode, Google AI Overviews, Gemini, Microsoft Copilot, DeepSeek, Meta Llama, Grok, and Claude, monitored up to hourly.

Yes. Every product line is monitored as its own entity with its own prompts, competitors and dashboard. Workspace View rolls them into one portfolio read with per-product movers, so nothing is hidden inside a blended average.

Yes. GrackerAI MCP exposes your visibility data to any Model Context Protocol client, including Claude, over a read-only connection scoped to the brands you authorize.

Yes. Single-tenant deployment on isolated infrastructure, SSO and SAML, approval workflows before anything publishes, and a Brand Voice profile whose never-say rules are enforced as hard constraints on generated content rather than treated as style preferences.

Every finding in the platform has an Add Task button. The task inherits the source context and a what-to-do checklist, takes an assignee, a priority and a due date, flags itself when overdue, and de-duplicates against what already exists. That is what keeps a 1,000-prompt program manageable for a marketing team of five.

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