Services

We engineer your brand
into AI answers.

We don't do content marketing. We don't do traditional SEO. We engineer your brand into the retrieval layer of AI systems — through Adaptive RAG, Brand Memory, and entity intelligence.

The Shift

Retrieval vs. Ranking.

AI models don't rank pages. They retrieve entities. If your brand isn't structured as a trusted entity, you don't get cited.

Dimension Traditional SEO RAG Signal / GEO
GoalGoogle ranking, clicksAI citations, brand mentions
Optimizes forKeywords, backlinksEntity clarity, retrieval signals
Measured byRankings, trafficCitation rate, prompt presence
MethodologyContent volume, linksAdaptive RAG, Brand Memory
TimelineMonths to yearsMeasurable in 90 days
Capabilities

Proprietary engineering.

Brand Memory™

Our proprietary knowledge layer maps your entity relationships and proof points into a format AI retrieval systems read, trust, and cite.

Adaptive RAG

We engineer retrieval signals — structured data, entity reinforcement, and source weighting — to ensure high retrieval priority across all major AI models.

PhD Method

Built on academic research into LLM retrieval behavior. We don't guess — we apply verified engineering principles tested on our own brand first.

Prompt Reality Audit

We test the real prompts your buyers use and capture how AI currently answers — including who it names instead of you and why.

Competitor Monitoring

We track which competitors are being cited in your category and identify the signals they're using that you're not.

Citation Delta Reporting

We rerun the same prompts at day 30, 60, and 90 — scoring the delta and keeping the system adaptive instead of static.

The Process

Five steps. One system.

01 / MAP

Prompt Reality Audit

We test the real prompts your buyers use and capture how AI currently answers — including who it names instead of you.

02 / BUILD

Curate Brand KB

We build and maintain a curated brand knowledge base so the right facts, entities, and proof stay retrievable.

03 / WEIGHT

Source Trust Scoring

Owned, earned, structured, expert, and third-party signals are weighted differently inside the retrieval layer.

04 / REINFORCE

Entity Memory

We strengthen brand-role-category consistency so models read your brand with clearer confidence and cite it more often.

05 / MEASURE

Citation Delta

We rerun the same prompts, score the delta, and keep the system adaptive instead of static.

Signal Architecture

Five dimensions of AI visibility.

Every brand is scored across five retrieval dimensions. We identify which are weak and fix them in order of impact.

Entity Clarity High Impact

How clearly AI models understand who you are, what category you're in, and what role you play.

Source Trust High Impact

The credibility and diversity of sources that mention your brand — owned, earned, structured, and third-party.

Retrieval Signals Medium Impact

Structured data, schema markup, and technical signals that help AI systems parse and retrieve your brand correctly.

Brand Memory High Impact

The curated knowledge layer that stores your brand facts, proof points, and entity relationships in a retrievable format.

Freshness Medium Impact

How recently your brand signals have been updated — AI models weight recent, consistent signals more heavily.

Start here

Every engagement starts
with a free audit.

We test real buyer prompts across ChatGPT, Claude, Perplexity, and Gemini — and show you exactly where you're missing. No commitment required.