Authority engineered for
Google and AI is a
data science
problem.
Most agencies are not data science companies.
Google doesn’t count links. It computes crawl probability, entity authority, retrieval confidence.
The DR score your agency reports is a proxy. Proxies break down exactly where precision matters most.
LLMs
LLMs don’t think in backlinks. They think in citation clusters, co-citation frequency, entity authority. If your brand isn’t inside the clusters LLMs have already formed, it doesn’t get cited.
Agencies
Most agencies have no methodology for either system. The metrics they report (Domain Rating, link count, keyword position) are proxies built for an older model of search. Google and AI compute authority differently. They aren’t equipped to measure it, let alone engineer it.
WLDM was built for the
model that does.
We map the authority layer of the internet.
We design citation systems for generative search.
We engineer AI citation probability.
Two retrieval systems run on authority. Google computes ranking probability. LLMs compute citation probability. WLDM engineers both.
We don't just build links. We engineer ranking probability.
Every link changes crawl probability, entity association strength, and ranking probability simultaneously. WLDM selects each using ML: BERT entity extraction, cosine similarity scoring, five classifiers at 99%+ accuracy across 18,000+ domains. Not outreach.
Authority graph construction.
Key Stat:
~50% traffic increase within 1–2 months across Citation Engineering clients
We engineer your brand's position inside AI citation clusters.
LLMs form stable citation clusters. 10–20% of citations consistently reappear together across prompts. WLDM maps these clusters using harmonic centrality and semantic similarity, then engineers your brand into them. 2 million citations analysed. The world’s first AI Citations Outreach Service.
Key stat:
Rank #1 on Google = 47% probability of AI citation. Rank #10 = 0%.
The research is ours.
The results are our clients'.
AI citations analysed through data science
ML model accuracy across 5 classifiers
Value of an AI visitor vs. a traditional organic visitor
Probability of AI citation at Google rank #1
Overlap between ChatGPT results and Google SERP.
ChatGPT session duration vs organic
WLDM Research Lab
We didn't just study how Google and AI work. We built the infrastructure to engineer it.
Two services. One ML pipeline.
Citation Engineering — BERT entity extraction, cosine similarity scoring, five-model classification at 99%+ accuracy. Not outreach. Authority graph construction.
AI Citation Engineering — harmonic centrality mapping, semantic similarity analysis, co-citation cluster targeting. 2 million citations analysed. The world’s first AI Citations Outreach Service.
Deployed for Fortune 500 and private equity. The methodology is not theoretical. It is infrastructure.
The methodology is not theoretical. It is infrastructure.
BUILT ON RESEARCH NO OTHER AGENCY HAS.
From below rank 30 to #1 for
"Online Casino."
10 months. ML-driven. No shortcuts.
“Online Casino” — 85,000 monthly searches, keyword difficulty 95, $549,000 in monthly traffic value, requiring approximately 1,400 referring domains to compete in the top 10.
This is not a keyword you stumble into. This is a keyword you engineer your way to.
Stake.com engaged WLDM to take them from below position 30 to the top. Using ML-driven Citation Engineering — selecting citation pathways based on page-level traffic, topical relevance, and cosine similarity — we constructed the authority graph required to rank and hold it. Position #1 achieved within 10 months. Non-brand organic traffic doubled in 90 days.
“Within 90 days of engagement, WLDM’s strategic link acquisition efforts helped us secure #1 positions for several ultra-competitive keywords and doubled our non-brand organic traffic.” — Peter Macinkovic, SEO Lead, Stake.com
Our Trusted Clients
Peter Macinkovic
Stake.com
Rob Barry
Hike & Byke
Jesse Schoberg
DropInBlogWe start with your data.
Not a pitch deck.