What is an entity in the context of AI visibility?
An entity is a uniquely identified concept — in this case, your business — that AI engines use as a structured reference point rather than treating your brand name as a plain text string. Google's Knowledge Graph, Wikidata, and similar databases store structured facts about entities: name, industry, founding date, location, related organisations, and more. When AI engines process queries, they resolve brand references to known entities and draw on all associated structured data. A business that is not established as a recognised entity, or whose entity data is incomplete, is at a systematic disadvantage when AI engines are deciding which brands to include in their responses.
What is schema markup and why does it matter for AI?
Schema markup is structured data — typically written as JSON-LD — embedded in your website's HTML that describes the contents of each page using a standardised vocabulary from Schema.org. It tells AI crawlers explicitly whether a page contains a product, a service, an article, a FAQ, a business listing, or other content type. AI engines use schema markup alongside entity data to form a more accurate understanding of your website's content. Invalid, incomplete, or missing schema means AI engines must infer meaning from unstructured text, which is less reliable and less comprehensive than reading correctly implemented structured data.
What are the 25 sources covered in the entity audit?
The 25 sources include Wikipedia (English edition and relevant Australian content), Wikidata, Google Knowledge Graph, Google Business Profile, ABN Lookup, ASIC company register, Crunchbase, LinkedIn Company Pages, Yellow Pages Australia, True Local, Hotfrog, Yelp AU, Apple Maps, Bing Places, Facebook Business Pages, industry association member directories, Australian news archives, government tender registers where relevant, review platforms specific to your industry, and additional structured databases AI engines are known to use for entity resolution. The exact list is adapted to your specific business category and geographic footprint.
How long does the audit take?
The Entity & Schema Audit is completed within 7 to 10 business days from receipt of your brand information brief. Delivery includes the full coverage map, schema crawl, validation report, and priority fix roadmap as a single packaged deliverable. For large e-commerce websites or businesses with unusually complex multi-brand entity structures, we advise on any timeline adjustment before starting.
What does the audit cost?
The Entity & Schema Audit is priced from AUD 1,200 for a standard Australian business. Final pricing depends on website size and entity footprint complexity. We provide a fixed-fee quote after a brief scoping call. There are no ongoing fees attached to this engagement — it is a one-time diagnostic.
What happens after the audit?
After delivery you can implement the fix roadmap using your own team, using the detailed correction instructions included in the report. You can engage Ignited Nepal to implement the fixes as a separate project. Or you can use the audit as the foundation for a broader AI visibility programme — feeding the findings into a GEO content strategy, entity authority building, or brand answer accuracy work. The audit is designed to be actionable as a standalone deliverable, and it also integrates directly with every other AI visibility service Ignited Nepal provides.
