AI Discoverability Strategy · F&B + Hospitality
AI doesn't rank
brands.
It selects them.
When someone asks AI where to eat or which brand to buy, you either appear — or your competition does.
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The Recommendation Layer
Most premium brands are invisible
in the moments that matter most.
Most premium food, beverage, and hospitality brands are invisible in those moments — not because they lack quality or credibility, but because AI systems can't find the structured signals they need to recommend them with confidence.
AI systems learn from human sources. Someone has to understand which sources matter in your category, what they're saying about your brand, and how to close the gap between how AI describes you and how your best customers would.
The work starts with a diagnostic — a precise investigation into where you stand in AI recommendation results today, why your highest-visibility competitors are winning the moments you should own, and exactly what needs to change. The output is a clear picture of where you stand and exactly what to do next.
For brands ready to act on the findings, an ongoing retainer builds the authority signals — content, third-party authority, competitive positioning — that move you from invisible to recommended, tracked with a quarterly re-audit so progress is never abstract.
"Every time someone asks an AI for a recommendation in your category, a draw happens. The brands with the most tickets win the most often. Each fan-out query your brand appears in is a ticket. Your competitors are winning because they have more tickets."Mike King · Two-time Search Marketer of the Year, iPullRank
Services
Every engagement starts with
a diagnostic and builds from there.
Find out where you stand, understand why, and build the signals that move you into the recommendation moments you're missing. Most engagements begin with the Diagnostic — a three-part investigation that establishes your current AI visibility position, surfaces exactly what the visible competitors are doing that you aren't, and delivers a prioritized roadmap for closing the gap.
A three-part investigation: where you stand in AI recommendation results today, why the visible competitors are winning the moments you should own, and a prioritized roadmap to close the gap. Minimal engagement required on your end.
Structured execution against the highest-impact gaps from your Diagnostic. Authority content, targeted brand selection infrastructure actions, technical improvements, and monthly visibility reporting with a quarterly re-audit to track position gained.
Focused competitive movement. Where the Visibility Retainer builds your presence, the Displacement Retainer targets the recommendation positions your competitors currently hold and builds the signal infrastructure required to take them — 30-day displacement cycles.
Active Engagements
Clients In Progress
Current engagements underway. Case studies published when re-audit results are available.
Original Research
AI Recommendation Patterns
Original data on how AI systems currently classify premium F&B brands — by category, by platform, by intent cluster.
The Modern leads at 1,361 total mentions — but 55% come from Gemini alone. Jean-Georges ranks 9th overall and surfaces only 6 times on Perplexity. New York is the most AI-contested fine dining market in the country.
Read the report →Four brands have captured the category in AI — and the gap to the rest of the field is nearly 350 mentions. Claude is a systematic blind spot for emerging craft brands. Perplexity is a leading indicator for brands too recent for training-data models.
Read the report →Domaine Serene has 21 Claude mentions with 481 total. Soter has 13 Claude mentions with 412 total. No single winery dominates cross-platform — the most competitively open wine country dataset in the series.
Read the report →Free AI Visibility Audit
Curious where
your brand stands?
Enter your brand name and category — you'll have a scored report in under 2 minutes.
About Ally
Lived on both sides
of the line.
Most consultants working in AI search have never sold a product on a shelf. Most consultants working in premium food and beverage have never thought seriously about how AI systems form opinions. This practice exists in the gap between those two worlds.
I spent 12 years in premium food and beverage — Italian wine importing, Napa Valley wineries, and building Nespresso's partnerships with the James Beard Foundation and Michelin Guide. I've worked the floor as a sommelier at a two-Michelin-star restaurant in San Francisco.
I spent the following 5 years at NetSuite earning President's Club, selling enterprise software to growing CPG companies. That's where I learned how the operational and commercial infrastructure behind premium brands actually works — and where I first started watching AI reshape how buyers find and evaluate products.
What that means in practiceI don't translate AI jargon into F&B language, or F&B nuance into generic marketing strategy. I work at the intersection because I've lived on both sides of it. The Signal Engineering framework I use isn't borrowed from B2B content strategy or generic SEO practice. It was built from the specific way premium F&B brands earn authority.
I'm selective about who I work with because this work only works when there's something genuinely distinct to build on. The brands I do my best work for have a real point of view, a differentiated product, and a founder who understands that brand identity is the raw material that makes AI recommendation possible.
Full background →