Client Engagements

Different Industries. Same Structural Gaps. Same Framework.

AI Advisory's methodology is industry-agnostic. The Citation Gap problem is structural, not sector-specific — and so is the solution.

B2B Manufacturing

A $100M+ Global Manufacturer

Market leader in precision measurement technology with strong Google presence but invisible AI engine footprint. Strong domain authority, weak AI recommendation presence.

Before
Not appearing in category queries across any AI engine
After
Cited in high-intent queries across all 4 engines
AI Advisory client engagement, 2024
"Their product pages ranked well but weren't being cited. We developed a content strategy specifically architected for AI engine recognition — not clicks."
DTC Beauty

A DTC Beauty Brand on Shopify

Growing direct-to-consumer brand with strong social presence, competing against established players in consideration-phase AI queries.

Before
Invisible in "best" and comparison queries across AI engines
After
Now surfacing alongside category leaders in AI recommendations
AI Advisory client engagement, 2024
"Different industry, same structural gaps. Low Citation Readiness, inconsistent cross-engine presence, content built for browsing not recognition."

The Structural Gaps Are Always the Same

Whether it's precision manufacturing or DTC beauty, the three structural gaps that prevent AI recommendation are identical across every industry we've audited.

Low Citation Readiness

Content structured for human browsing, not AI extraction and recognition

Inconsistent Cross-Engine Presence

Visible on one engine, absent on others — no systematic multi-engine strategy

Weak Entity Architecture

AI engines lack the confidence signals needed to recommend with certainty

See Where You Stand