Building an entity that AI search could find

Building an entity that AI search could find

The company ranked. It just did not exist as a recognised entity, and in public-sector procurement that reads as a credibility problem rather than a marketing one.

What the client was dealing with

A global provider of cloud-native, AI-powered emergency communication and call-handling software sells into agencies replacing legacy 911 infrastructure. Those are procurement-led buying committees who research a vendor privately long before anyone fills in a form.

The company had rankings. What it did not have was an entity record. Branded searches returned no Knowledge Panel and almost no sitelinks, so a buyer checking the vendor's legitimacy found a thin result where an established supplier's profile should have been. The team had been treating this as an SEO scoring problem. It was a recognition problem, and the two need different work.

Pew Research Center tracked 68,879 real Google searches and found users clicked a traditional result 8% of the time when an AI Overview was present, against 15% when it was not. For B2B technology queries, AI Overviews now trigger on the large majority of searches. Pew Research Center, 22 July 2025. Trigger rates from aggregated 2026 industry tracking.

How the engagement ran

01  Discover

Mapped the commercial goal, the buying committee, the existing stack and the baseline. Recorded what branded search returned across three markets before touching anything.

02  Diagnose

Rankings were adequate; entity resolution was absent. Schema, third-party profiles and authoritative mentions were inconsistent, so nothing consolidated the company into a single record.

03  Design

Built the entity architecture, the answer-first content plan, the paid channel role and the measurement model, with metrics and sources agreed in writing before work started.

04  Deliver

Aligned schema and sameAs references, corrected listings and citation sources, published answer-first content, and ran LinkedIn against target buyer roles while the entity work matured.

05  Develop

Supported the HubSpot integration so lead data landed in one place, then documented the workflow and trained the internal team to run it.

06  Demonstrate

Reported against agreed KPIs with baselines and windows attached to every figure, and used the evidence to set the next cycle's priority.

Engagement detail

FieldDetail
SectorIT & SaaS · Emergency communications
MarketUnited States, public sector
DurationSix months, entity results visible from month three
ServicesEntity and AI search visibility, technical SEO, content, LinkedIn paid, CRM enablement
SystemsSearch Console, GA4, HubSpot, LinkedIn Campaign Manager
HandoverDocumented workflow, internal team running independently

Not sure whether your problem is ranking or recognition

Most teams diagnose one and spend on the other. A short diagnostic tells you which constraint is costing you pipeline.

Client anonymised at the client's request.

Related service: To turn your own team's expertise into published articles, see our blog writing service.

Frequently asked questions

Why did the company lack visibility despite ranking?

It had rankings but no entity record: branded searches showed no Knowledge Panel and few sitelinks, which reads as a credibility problem to procurement buyers.

What is entity work in SEO?

Aligning schema and sameAs references, correcting listings and citation sources and publishing answer-first content, so search systems consolidate the company into one record.

Why does entity recognition matter in public-sector sales?

Procurement-led buying committees research vendors privately before making contact, so a thin branded result undermines credibility.