AI Search
Ambiguity is the cheapest thing to fix and the most expensive to ignore.
Remove every doubt about what your brand is, what it does and what it is connected to.
Search engines and language models both work with entities: things with names, attributes and relationships. If your brand name is written three ways, your category is described differently on every page, and your own site contradicts your LinkedIn, both systems have to guess - and they guess separately.
Entity work is unglamorous and it unblocks more than it looks like it should.
What it covers
- Consistent brand, product and person naming across all properties
- Organization, Person and Product structured data
- Third-party profiles and knowledge sources alignment
- Disambiguation from similarly named companies
Also in this capability
- AI Visibility AuditFind out when AI recommends you, when it recommends your competitors - and why.
- GEOGenerative Engine Optimization: the work that makes your content usable as an answer.
- LLM OptimizationMake your site readable, retrievable and safe to quote for language models.
- AI Brand MonitoringContinuous measurement of what models say about you, in which context and on what basis.
How it works
01
Find out what you are called, rather than deciding it
Name variants cannot be established in theory. The first measurement shows which forms models actually use for you - and it regularly includes one nobody in the company writes.
02
Pick one spelling and enforce it everywhere
Site, LinkedIn, directories, press materials, invoices. Every additional form splits your signal in two and, in competitor sets, splits your measured share as well.
03
State the boring facts explicitly
What you do, for whom, where, since when, on what terms. These are the sentences a model needs and the ones brand pages most often replace with atmosphere.
04
Disambiguate from everyone you can be confused with
Similar names, a former name, a company in another country. Structured data and consistent co-mentions give both search engines and models enough to tell you apart.
What you get
- List of name forms models actually use, from measurement
- One canonical spelling, applied across every property you control
- Organization, Person and Product structured data
- Corrections sent to third-party profiles and directories
- Disambiguation plan against similarly named companies