The three jobs AIVZ does — and how each one works. From the 93 factors we measure, to the integrations we route through, to the fixes we apply directly on your stack.
Before you fix anything, you have to know what's broken. AIVZ runs every URL through a 93-factor scoring model — across the AI Visibility Stack, the 34 authority signals, and 6 major AI platforms — and tells you precisely where your visibility is failing.
The most comprehensive AEO measurement framework in the market. 93 factors across 9 categories spanning access, structure, trust, authority, and observability. Every factor carries a confidence label so you know what's proven and what's still being validated.
Read the full taxonomyEvery AI visibility decision happens in three layers, in dependency order: Access (can AI crawlers reach the content?), Understanding (can AI parse the structure?), Extractability (can AI cleanly isolate the answer?).
See the AI Visibility StackA page can score 78 for Google AI Overviews and 45 for ChatGPT — because each platform values different structural signals. AIVZ scores readiness separately for the six major AI engines.
Citation isn't just about what's on your page. AIVZ measures authority at the org and person level — 20 organizational signals (backlinks, brand mentions, knowledge graph, reviews, certifications, app store ratings) and 14 person-level signals (podcast appearances, published books, GitHub presence, conference speaking, LinkedIn authority, course instruction). These feed the Authority Rank engine — a graph-based scoring algorithm adapted from PageRank for personal and organizational credibility.
You get: an AI Visibility Score (0–100), per-platform readiness scores, layer-by-layer breakdowns, and an authority assessment — all on a single dashboard you can share with your team or your client.
Knowing what's broken is half the job. Knowing what to fix first — and getting it to the right person, system, or workflow — is the half that actually moves the score. AIVZ prioritizes every fix by impact, and routes it to the surface where the work actually gets done.
Every fix comes with three things: the impact (projected score recovery), the effort (one-line schema add vs. full content rewrite), and the dependency (Access before Understanding before Extractability). The result: "Fix these 3 things to gain 18 points" — concrete, actionable, ordered.
Schema, FAQ blocks, llms.txt → applied to the CMS. Author bylines, credential markup → routed to the content team. Citation alerts → routed to Slack or Teams. Stakeholder reports → scheduled into Looker Studio or branded PDFs.
Currently Live: Search Console, GA4, HubSpot, GoHighLevel, Slack, Teams, Looker Studio, Zapier, Make. Each integration is purpose-built for orchestration — not just data export.
See all integrationsAgencies running AIVZ across 10–100+ client domains get an orchestration layer purpose-built for that scale: per-client credit budgets and usage tracking, account-manager assignments, bulk domain import, scheduled scans, white-label branded reports, client-portal invite links — clients see their own dashboard, never AIVZ branding.
You get: a prioritized fix queue, routing into your existing stack, automated reports for stakeholders, and (for agencies) a full multi-tenant orchestration system. The score doesn't move on its own — but everything that needs to happen for it to move is queued, routed, and visible.
Most AEO tools stop at recommendations. AIVZ is the Command Center because it doesn't just tell you what to fix — it executes the fix directly via per-platform adapters, native content orchestration, and delegated MCP/CLI work for headless or brand-voice tasks.
| Platform | Status | What we do |
|---|---|---|
| WordPress | Live | Native execution via the AnswerEngineWP adapter — schema markup, llms.txt manifests, FAQ blocks, meta descriptions, summary blocks, priority fix queue. The score moves while you watch. |
| Shopify | Beta | Orchestrated execution via MCP/CLI adapter. |
| Wix | Beta | Orchestrated execution via MCP/CLI adapter. |
| Webflow | Beta | Orchestrated execution via MCP/CLI adapter. |
| BigCommerce | Beta | Orchestrated execution via MCP/CLI adapter. |
| Headless | Beta | Orchestrated execution via MCP server + CLI for any custom or headless stack. |
| Squarespace | Roadmap | Coming soon — no execution yet. |
WordPress is our flagship execution surface — the most mature adapter and our GTM wedge. Shopify, Wix, Webflow, BigCommerce, and Headless are in Beta. Squarespace is on the roadmap.
For every supported surface, AIVZ generates and applies the structural content AI systems need to extract and cite: schema markup, llms.txt manifests, FAQ blocks, meta descriptions, summary blocks, answer-block formatting. This closes most extractability gaps natively, automatically, and at scale.
For brand voice, longer-form rewrites, or custom development workflows, AIVZ delegates to your tools of choice via the Model Context Protocol or our CLI. Long-form rewrites → Claude Code, Cursor, or your team's preferred LLM. Brand-voice → your voice-and-tone system. Custom CMS → for any platform without a native adapter.
A deliberate boundary, for trust. No social media posts — that's not AEO. No fabricated stats or testimonials — citation requires real signals. No ad copy — wrong category. AIVZ generates structural content and orchestrates content workflows. We're not a general-purpose AI writer.
You get: fixes applied directly on your stack (Live for WordPress, Beta for Shopify/Wix/Webflow/BigCommerce/Headless), native content orchestration, and delegated workflows for what requires human-in-the-loop. The score doesn't just have a fix path — the fixes actually run.
Most AEO tools are one-time audits. You scan, you get a report, you implement, and the next time you check, the platforms have shifted and your report is stale. AIVZ is built differently — Diagnose, Orchestrate, and Execute close into a continuous loop.
Every observation feeds back into the Diagnose layer. The score isn't a snapshot — it's a moving signal.
This is the difference between AEO as a project and AEO as ongoing intelligence. Platforms change. Algorithms shift. Competitors optimize. A one-time audit is obsolete the moment it finishes. The Authority Loop is what keeps AIVZ relevant after the first scan, and what makes the Command Center positioning real instead of marketing.
Google organic ranking explains only 8–28% of AI citation behavior — depending on the platform. ChatGPT especially draws from different sources. AIVZ measures the other 72–92%, alongside the SEO tools you already use. Most agencies and SEO teams run AIVZ alongside SEMrush or Ahrefs. Different signal set, not a competing product.
See how AEO compares to SEORun a free scan. Diagnose your AI visibility, see your fix path, and decide where to start.
Or book a demo to see the Orchestrate and Execute layers in action.
