THE WORKFLOW

Three steps.
On repeat.

Explore your store through every AI model, fix what blocks agents, then re-optimize as the models change. Your team approves every change.

Up to 40% of online shopping is moving to AI agents. Every month you wait, they learn to pick someone else.

01 // EXPLORE

STEP 01 // EXPLORE

Explore

See your store the way every AI agent sees it.

✓ Page-by-page crawl: REVVDA reads the HTML of every product and category page, the way AI crawlers do.
✓ Many models, one view: real buyer questions asked to 19 AI agents, so you see how each one reads you and who it names instead.
✓ AI readiness check: each page gets a readability diagnosis and the schema it is missing.

AI CATALOG SCAN · EXAMPLE In progress

Reading product and category pages…

10,989 URLS EXTRACTED

PRODUCT SCHEMA (JSON-LD) VALIDATED ✓

{
  "@type": "Product",
  "name": "Pima Cotton Pajama Set",
  "brand": "Premium Loungewear",
  "material": "100% Pima Cotton",
  "availability": "InStock",
  "priceCurrency": "USD"
}

STEP 02 // FIX

Fix

Clear fixes, ranked by impact, and the tools to ship them.

✓ Copy agents can quote: concrete product facts in short sentences, reviewed by your team before they go live.
✓ Semantic schemas: verified Schema.org blocks, published to your CMS in one click once your team approves, so agents read your data without guessing.
✓ Human sign-off: each fix goes Understand → Fix → Create task, and your team approves it.

EVERY RUN, ON A SCHEDULE

EXPLORE → FIX → VERIFY ✓ → REPEAT ↻

STEP 03 // RE-OPTIMIZE

Re-optimize

Not a one-time audit. AI models keep changing, so your store has to keep up. REVVDA does it for you.

✓ On a schedule: re-crawls and visibility runs repeat automatically.
✓ Verified by scan: every shipped fix is checked, run after run.
✓ Always a next step: new issues and model changes land in your queue, ranked again.

THE GEO SCORE, EXPLAINED

What makes a page easy for AI to cite.

The GEO score combines four signals. Each one points to a concrete fix.

Data

Structured data

Does the page speak in schema.org markup (product, price, availability, brand, FAQ)? Structured data is how engines extract facts without guessing.

Typical fix: add or complete the page's JSON-LD.

Quote

Quotability

Does the page contain short, self-contained factual sentences and expert statements that an engine can lift into an answer as they are?

Typical fix: add citation-ready proof blocks and clear one-sentence answers.

Facts

Factual density

How many concrete, checkable details does the page give: materials, dimensions, origin, certifications, care, comparisons? Vague copy gives AI nothing to recommend.

Typical fix: enrich descriptions with verifiable attributes.

Semantic

Page structure

Is the HTML built with meaningful tags (main, article, section, figure, nav, structured h1) so engines can distinguish content from menus and footers?

Typical fix: update the page template once, improve every page at once.

WHAT REVVDA DOES FOR YOU

Eight actions that turn findings into results.

Click an action to see what your team gets.

Diagnose

Understand

See why AI agents recommend someone else.

In REVVDA: Visibility

See it on your site →

Change your store. Or be lost.

Every store must be rebuilt for AI agents. Pay as you go: start with 90 days for $99, then pay for the capacity you use.

See plans & pricing

Three steps. On repeat.