Be the answer AI gives.

Answer accuracy

Every AI answer is broken into claims and checked against your fact sheet. Wrong addresses, old offers and made-up services are grouped into issues, with the page that caused each one.

Citations and sources

See the domains and pages the engines build their answers from. Directories, review sites, listicles, Reddit threads, your pages and your competitors' pages.

Question research

People Also Ask, autocomplete, Reddit threads and your own enquiries, turned into prompts and content.

Share of voice

Weighted by position, so being named first counts for more. See who the engines recommend instead of you, and why.

Content opportunities

Page two keywords, falling pages and AI answer gaps, each with an outline and the facts to use.

Schema and entities

Copy-paste JSON-LD for the types a page is missing, and an entity audit that shows how machines read your brand.

{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "@id": "https://northwind.example/#leeds",
  "name": "Northwind Kitchens Leeds",
  "parentOrganization": {
    "@id": "https://northwind.example/#org"
  },
  "address": {
    "@type": "PostalAddress",
    "addressLocality": "Leeds"
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.8"
  }
}

Work with measured outcomes

Findings become tasks with their evidence attached. The platform records a baseline and checks later whether the change worked.