We reverse-engineer how language models retrieve and synthesize web content, securing direct brand recommendations across Google AI Overviews, ChatGPT, Claude, and Perplexity.
Direct evaluation of your brand's AI search footprint, citations, and model recommendations across Google AI Overviews and ChatGPT.
"Dan Petrovic made a super write up around Chrome’s latest embedding model with all the juicy details on his blog. Great read."
"We were given our very own bespoke internal link recommendation engine that leverages world-class language models and data science. It changed my perspective on what’s possible in enterprise SEO."
Measured outcomes across 6,776 tracked AI answers evaluating commercial custom sportswear recommendations in competitive generative search.
| Metric | Apr 15, 2026 Baseline | May 31, 2026 Result | Percentage Points Up | Total Percentage Increase |
|---|---|---|---|---|
| Share of Voice | 2.18% | 3.87% | +1.69 | +77.52% |
| Mention Share | 2.06% | 4.37% | +2.31 | +112.14% |
| Citation Share | 2.30% | 3.38% | +1.08 | +46.96% |
We deliver five specialized commercial workstreams engineered to capture high-intent brand recommendations across generative search.
We structure brand entity profiles, digital PR citations, and authoritative web consensus so conversational language models recommend your business when prospects evaluate your category.
We re-engineer content hierarchies into declarative summaries, structured comparison tables, and factual data points that Google's Gemini retrieval models extract for answer snapshots.
We manage crawler access policies for AI retrieval bots, build comprehensive multi-entity JSON-LD Schema graphs, and deploy machine-readable content endpoints including llms.txt.
Using proprietary mathematical rankers, we test and refine passage length, entropy, and information density to maximize the probability that models quote your text once retrieved.
We systematically probe large language models to identify competitive misattributions, outdated pricing, or hallucinations, executing off-site entity realignments to correct model memory.
A comprehensive 30-day evaluation measuring baseline mention share across Google AI Overviews, ChatGPT, and Perplexity, complete with a prioritized engineering roadmap.
Each generative engine uses distinct retrieval architectures, citation thresholds, and context weights. We engineer specific entity signals for each major platform.
Optimizing passage extractability, structured tables, and Schema graph consensus for Google's multimodal Gemini models.
Structuring authoritative digital PR, verified entity profiles, and high-trust index signals favored by OpenAI retrieval.
Engineering real-time fresh citations, domain-specific authority, and web consensus for Perplexity's answer synthesis.
Aligning long-form technical documentation, machine-readable text files, and high-density domain data for Claude's reasoning models.
Competitors rely on generic manual prompts. DEJAN executes client campaigns using custom computational models and mechanistic interpretability tools.
Traditional SEO optimizes for where a page sits on a search results page. Our internal Content Optimizer engine optimizes for whether an AI grounding system chooses to quote your text.
When an AI assistant answers a question, it compares competing sources and selects the most quotable passage. Our agency team uses this custom ranker to iteratively refine target passages until models mathematically prefer your brand over competing sources.
Map Connections: We identify what models connect to your brand and what they connect to competitors, mapping the entities that define your category.
Connection Strength: We probe models to turn associations into probabilities, identifying which entities you own outright, which you share, and which belong to competitors.
Selection Optimization: We mine the sources AI systems retrieve and rewrite target passages until models prefer your page over competing sources.
Understanding the technical difference between indexing a document and being selected as a cited authority.
| Dimension | Traditional Ranking Algorithms | Generative Recommendation Engines |
|---|---|---|
| Primary Objective | Index placement on ten-blue-link results pages | Direct brand recommendation and citation in synthesized answers |
| Evaluation Signals | Inverted index keyword matching and PageRank link authority | Neural embeddings, entity co-occurrence, and semantic web consensus |
| Retrieval Architecture | Document-level relevance and crawl depth | Passage-level extraction, token entropy, and factual density |
| Target Crawlers | Standard web crawlers (Googlebot, Bingbot) | AI retrieval crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) |
DEJAN has delivered search campaigns from Australia since 2008. The company is registered in Queensland and operates a senior distributed team across Brisbane, Sydney, Melbourne, and Perth.
Market context matters more in AI search than it did in ranked search. The sources a language model retrieves to answer an Australian buyer are not the sources it retrieves for the same inquiry in the United States. A brand can dominate citations in North America while remaining invisible in Australian search results.
Every measurement we report is isolated by market. The question we answer for Australian enterprises is whether Google AI Overviews, Gemini, ChatGPT, and Claude name you when a domestic buyer asks for a recommendation in your category. We engineer visibility around Australian English search semantics, domestic competitor entity graphs, and strict Australian Privacy Principles (APPs) governing client data in AI model evaluations.
DEJAN employs an all-senior team of search strategists, computational linguists, and technical engineers based in Australia.
Dan Petrovic
Founder & AI SEO
Mike Jolly
Strategy Director
Martin Reed
Technical SEO
Public Relations
Senior SEO
Senior SEO
Senior SEO
Senior SEO
Operations
CFO
Developer
PPC Strategist
Technical SEO
Outreach
Transparent engagement models tailored for mid-market and enterprise organizations competing for conversational search share.
A full diagnostic of your brand's existing AI search footprint and competitive entity gap.
Comprehensive ongoing Generative Engine Optimization to establish brand recommendations in AI models.
Dedicated engineering and data science engagement for multi-brand and international enterprises.
Common commercial and technical questions regarding AI SEO engagements.
AI SEO at DEJAN starts at $5,000 AUD per month (plus GST for Australian clients). Our standalone Strategic AI Search Audit is also $5,000 AUD (+ GST), matching one month of retainer. Scope is determined by the number of entities tracked, the target geographic markets, and required technical implementation.
On-site structured data fixes, content extraction updates, and crawl directives often reflect in AI answer citations within two to four weeks. Off-site entity building and broad consensus realignment typically compound over three to six months. In our OWAYO campaign, brand mention share rose from 1.5% to 8.0% over four months across 6,776 tracked AI answers.
DEJAN SEO PTY LTD is an Australian company, ABN 77 151 340 420, registered in Queensland and running search campaigns since 2008. The team works remotely from Brisbane, Melbourne, Sydney, and Perth. We conduct meetings via video conference, serving Australian and global enterprises.
Yes. Generative search engines assemble their answers directly from retrieved web pages. The pages an AI model can find, read, and trust determine which brands it recommends. While keyword rankings no longer tell the whole story, technical search indexability remains the foundation of all AI retrieval.
AI agents excel at mechanical execution: crawling, log analysis, schema generation, entity mapping, and internal link modeling. They are unreliable on commercial judgment: which entities a brand should own, why a model associates a competitor with your category, and what content to publish. We build custom agents, and senior strategists sign off on all client recommendations.
No legitimate agency can guarantee inclusion inside third-party language models. DEJAN uses mechanistic probing and mathematical optimization to align digital assets with the exact retrieval criteria search models require, maximizing citation probability.
Do not leave your brand's conversational visibility to algorithmic chance. Schedule a confidential strategy session with our senior Australian search team.
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