Be the source the answer cites, not the link below it

AI Overviews now appear above the results on essentially every commercial query we test, including the ones where we rank in the top three. Ranking is no longer the same as being seen. We measure how assistants describe you, fix what makes you citable, and track whether it worked.

In plain terms

What Generative Engine Optimization means in practice

Brainforge delivers generative engine optimization services. We measure how AI assistants describe you, fix the entity and structured data gaps, and build content that gets cited in AI answers rather than buried below them.

Where teams get stuck

Measure AI answer visibility, fix entity and structured data gaps, and earn citations instead of impressions.

We rank well and still see almost no clicks because an AI answer takes the query.

We do not know what AI assistants say about us, or whether they cite us at all.

Our competitor gets quoted in AI answers and we do not, and we cannot see why.

Our structured data is missing or wrong, so assistants describe us inaccurately.

Nobody internally owns AI visibility, so it is nobody's job to fix.

What we deliver

Core Generative Engine Optimization

AI visibility measurement

A repeatable baseline of which queries carry an AI answer, whether you appear in it, and which sources the answer draws on.

Entity and structured data

Making your organisation, products, and expertise machine-readable so assistants can attribute claims to you correctly.

Answer-oriented content

Content structured for extraction, with the definitions, numbers, and comparisons answer engines actually quote.

Third-party presence

The sources AI answers draw from, including forums, directories, and partner pages, and what your presence there looks like.

How deep it goes

Capabilities behind the work

The same delivery primitives (context, controls, and review) show up across every engagement.

AI visibility measurement

Establishing what the answers currently say before changing anything.

AI Overview presence auditBrand and entity mention trackingCitation source mappingAnswer-content comparison

Entity and structured data

Making it unambiguous who you are and what you claim.

Organization and entity schemaProduct and service schemaFAQ and article markupConsistent naming and entity definitions

Answer-oriented content

Writing the thing the answer engine wants to quote.

Definition and comparison formatsOriginal data and named figuresExtraction-friendly structureTechnical accuracy review

Third-party presence

The sources the answers actually cite.

Source inventory for priority queriesForum and community presence reviewDirectory and listings accuracyPartner and co-marketing coverage

Measurement loop

So this is a channel with numbers rather than a one-off project.

Recurring answer-presence trackingQuery set maintenanceChange attributionReporting into existing channel reporting

The stack we build with

Tooling our team runs in production

Frameworks, platforms, and infrastructure we implement, integrate, and operate end to end.

SERP and answer measurement

DataForSEOValueSERPBright Data

Structured data

Schema.orgGoogle Rich Results TestCustom JSON-LD

Search performance

Google Search ConsoleBing Webmaster ToolsGA4

Content operations

docs-as-codellms.txt

What changes

Outcomes you can point to

A measured baseline of AI answer presence across your priority queries.
Structured data and entity definitions that make you citable and correctly attributed.
Content built for extraction, not just for ranking.
A view of the third-party sources the answers draw on.
A repeatable measurement loop so you can tell whether changes worked.

Proof in production

See where this work shows up.

Amplitude vs Mixpanel vs PostHog

A comparison page built for extraction rather than padding, which now ranks in the top ten for its primary query in a SERP that carries an AI Overview on every variant we tested.

See the comparison format we build →

Common questions

Generative Engine Optimization, straight answers

What is generative engine optimization?

It is the practice of being visible and correctly attributed inside AI-generated answers, rather than only in the ten blue links. In practice that means three things: measuring which queries carry an AI answer, making your entity and structured data unambiguous, and publishing content that answer engines can extract and quote.

How is GEO different from SEO?

SEO optimises for a ranking position. GEO optimises for being the source an answer cites and for being described accurately when it does. They share foundations, so good structured data and clear content help both, but the measurement is different and the tactics diverge.

Can you guarantee we will appear in AI Overviews?

No, and anyone promising that is guessing. What we can do is measure your current presence, fix the things that make you citable and misattributed, and show you movement over time on a fixed query set.

How do you measure AI visibility?

We maintain a fixed query set against your priority terms and record, on a cadence, which queries return an AI answer, whether you are cited, which sources are cited, and how the answer describes you. That produces a baseline and a trend rather than a one-off screenshot.

Does GEO replace our existing SEO programme?

No. In our own data, AI answers now appear on essentially every commercial query we test, including ones where we rank in the top three. That makes GEO an additional layer on top of SEO, not a replacement, and both need the same structured-data and content-quality foundations.

We are a small company. Can we compete in AI answers?

Often better than in classic paid-dominated SERPs, because answer engines reward specific, well-evidenced, clearly structured content over domain size in many categories. Original data and precise definitions are things a small team can produce.

How we work