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The Product

The Command Center for Answer Engine Optimization.

AIVZ measures, prioritizes, and executes the work that gets your content cited by AI systems. Across six AI platforms. Across the surfaces where your content actually lives.

93 factors 6 AI platforms 7 execution surfaces 9 integrations live
The operating model

Diagnose. Orchestrate. Execute.

Most AEO and AI-visibility tools stop at measurement — they tell you what's wrong and leave the fix work to your team. AIVZ is built around three beats: diagnose what's failing, orchestrate the prioritized fix path, and execute the work where the adapter coverage permits.

01

Diagnose

Comprehensive measurement across the 93-factor AEO taxonomy. Composite AI Visibility Score (0–100), three-layer Stack breakdown, six per-platform readiness scores, and Authority Rank for off-site signals.

  • Every measurement labeled by confidence
  • Every recommendation traced to a specific factor
  • Runs whether or not you use the rest of the platform
02

Orchestrate

Prioritized fix paths organized in dependency order — Access before Understanding before Extractability. Per-platform tuning surfaced separately when fixes have engine-specific optimal implementations.

  • Schedule-aware: weekly scans, citation event monitoring
  • Per-page recommendations grouped into actionable queues
  • Score-history tracking with regression detection
03

Execute

Native execution where AIVZ's adapter coverage permits — schema, content rewrites, FAQ blocks, summary blocks, meta descriptions, llms.txt manifests, robots.txt updates. Across seven execution surfaces.

  • WordPress Live; Shopify, Wix, Webflow, BigCommerce, Headless in Beta
  • Delegated execution via MCP/CLI for brand-voice work
  • The execution layer that makes "Command Center" operational

Together, the three beats turn AEO from an open-ended optimization project into a measured, prioritized, executable workflow. That's what makes AIVZ a Command Center rather than a measurement tool.

The capability surface

Four capabilities. One integrated platform.

The three-beat operating model surfaces through four core capabilities, each available at the appropriate tier.

Capability 1 — Measurement

What AIVZ measures.

The measurement capability is AIVZ's foundation — every other capability builds on the scan and score outputs.

Scope

One score. Three layers. Six platforms.

  • Composite AI Visibility Score (0–100) classified into four tiers: AI Authority (90–100), AI Extractable (70–89), AI Readable (40–69), Invisible to AI (0–39)
  • Three-layer breakdown per the AI Visibility Stack: Access, Understanding, Extractability
  • 93-factor taxonomy coverage across 9 categories with 4 confidence labels per factor
  • Per-platform readiness for ChatGPT, Google AI Overviews, Perplexity, Gemini, Microsoft Copilot, voice assistants
  • Authority Rank for off-site signal aggregation across 34 organizational and personal signals
  • Citation event monitoring for tracking AI citation start/stop events
  • Score history + regression detection for tracking changes over time
Full measurement capability detail
Tier scope at a glance
Capability Free Pro Agency Enterprise
Score + Stack breakdown
Per-platform readiness
93-factor detailTopFullFullFull
Authority Rank
Citation monitoring
Score history7 days90 days1 yearUnlimited
Capability 2 — Recommendations + Execution

The fix path, then the fix.

The recommendations capability turns scan output into a prioritized, executable fix sequence. The execution capability runs the fixes — natively where the adapter is Live, via delegated execution where deeper content work is needed.

WordPress
Live
Schema, meta, FAQ blocks, summary blocks, llms.txt, robots.txt, AEO score widgets — all native.
Shopify
Beta
Product schema, collection schema, FAQ blocks, meta description optimization (subset).
Wix
Beta
Schema markup, meta descriptions, structured content blocks (subset).
Webflow
Beta
Embedded JSON-LD schema, FAQ blocks via component substitution (subset).
BigCommerce
Beta
Product/category schema, meta description optimization (subset).
Headless / Custom
Beta
MCP server + CLI; bring-your-own-stack execution path.
Squarespace
Roadmap
Native adapter planned; not yet shipped.
Marketplaces
Documented
Optimization framework documented; native build pending.

For content work beyond AIVZ's native execution scope — long-form rewrites, brand-voice work, complex content reorganization — AIVZ delegates via MCP server integration to Claude, GPT, or Gemini. AIVZ orchestrates, the LLM executes, AIVZ verifies.

Even with delegated execution available, AIVZ refuses three categories: social media post generation, content with fabricated statistics, and pure ad copy. These aren't capability gaps — they're discipline boundaries.

Full recommendations + fix execution detail
Capability 3 — White-Label

Resell AEO under your brand.

The white-label capability is what turns AIVZ from a measurement tool into a resellable agency product. Available at Agency tier and above; full override of AIVZ-branded surfaces with the agency's own brand identity.

What's white-labeled
  • Custom domain hosting (your-aeo.your-agency.com)
  • AIVZ-branded UI replaced with agency's brand assets, logo, color tokens
  • Branded client portal — clients see your brand, never AIVZ's
  • White-labeled PDF reports with custom letterhead and contact info
  • White-labeled email templates for scan + regression notifications
  • API responses optionally proxied through agency-branded subdomains
What stays canonical

Tier names (AI Authority / AI Extractable / AI Readable / Invisible to AI), Stack layer names (Access / Understanding / Extractability), confidence labels, and tier color tokens are part of the published methodology. They stay in place under white-label.

This is intentional. Methodology consistency is what lets clients trust the score across providers. The methodology stays canonical; the brand wraps around it.

Full white-label + multi-tenancy detail
Capability 4 — Developer Surface

AIVZ fits the stack you already run.

AIVZ doesn't replace your existing SEO, content, or analytics stack. It plugs into it. 198 REST API endpoints, MCP server for LLM-direct integration, CLI for headless workflows, webhook events, and native integrations with the tools your team already uses.

Always-On (9 Live)

Search Console, GA4, HubSpot, GoHighLevel, Slack, Teams, Looker Studio, Zapier, Make. Connect once, AIVZ pushes scan data and score changes into the surfaces your team already monitors.

Self-Service Adapters

WordPress plugin (Live), Shopify app, Wix app, Webflow app, BigCommerce app, Squarespace app (Roadmap). Self-service install via the platform's app marketplace.

MCP Server + CLI

Claude, GPT, and Gemini can read AIVZ scan data and execute fixes via MCP. CLI for CI/CD-integrated AEO checks, automated scoring on deploy, and batch operations across many domains.

REST API + Webhooks

198 endpoints covering scans, scores, recommendations, fix execution, white-label config, and multi-tenant management. Tier-scoped webhook event taxonomy for push-based observability.

What's in each tier

Free, Pro, Agency, Enterprise.

AIVZ is offered at four tiers, each scoped for a different use case. Pricing is set at the pricing page; this surfaces capability scope.

Capability Free Pro Agency Enterprise
AI Visibility Score + Stack breakdown
Per-platform readiness (6 platforms)
93-factor detailHigh-impact subsetFullFullFull
Authority Rank
Citation event monitoring
Score history retention7 days90 days1 yearUnlimited
Scans per month5 credits5,00025,000100,000+
Domain count11050Unlimited
Team seats1310Unlimited
Native execution adaptersWordPressAll Live + BetaAll Live + BetaAll + custom
Delegated execution (MCP)
White-label + multi-tenancy
API accessLimitedFullFull
SSO / SAML
Dedicated CSM
SLABest effortStandardPriorityCustom
See tier pricing
Ready when you are

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