Build Your AI Search
Growth Engine

AI search optimisation focuses on influencing how large language models (LLMs) — like ChatGPT, Grok, Claude, Gemini and Perplexity — describe and recommend your brand. Traditional SEO optimises pages for Google's ranking systems. AI search optimisation optimises your entire web presence for LLMs that summarise, compare and recommend products. Key differences: • LLMs rely on consensus, not backlinks or SERPs • Research happens inside chat interfaces, not on Google • Users ask comparative and evaluative questions (e.g., "best X tools," "X vs Y") • LLMs pull from multiple domains, not just your site If you want to show up as the #1 recommendation in AI platforms, you need to optimise for how models understand your brand — not just how Google crawls your pages.

AI search has become the new top-of-funnel. Your customers now compare products directly within chat interfaces. If an LLM consistently recommends your brand as the best product in your category, you capture: • higher-intent traffic • more demo requests and sign-ups • stronger brand preference • increased conversion rates • more direct and branded search AI search optimisation gives you persistent visibility where buyers now make decisions, which compounds into predictable revenue.

LLMs base recommendations on a mix of: • consensus across the web • high-authority third-party content • up-to-date product comparisons • brand clarity and relevance • clean technical signals (schema, entities, accessible site architecture) They reward brands that are: • Consistently mentioned across multiple domains • Clearly positioned as leaders in their category • Technically easy to understand and index • Supported by bottom-of-funnel content In short: LLMs follow the internet's consensus, not your homepage.

You influence LLMs through: • Model-ready, bottom-of-funnel content (e.g., competitor comparisons, alternatives, best-of lists) • Multi-domain presence that reinforces your leadership • Clear technical foundations that help indexers interpret your product • Narrative correction where old or incorrect information is overwritten • Reddit and community signals that strengthen trust When these signals align, AI engines start describing your brand the way you want to be described — and position you above competitors.

Consensus engineering is the process of building agreement across the internet that your brand is the top choice in its category. LLMs don't rely on a single domain. They analyse: • third-party listicles • comparisons • publisher sites • Reddit threads • community discussions • expert commentary • structured data If these sources consistently signal that your brand is the best, AI models will amplify that narrative. Consensus engineering is the most powerful lever for ranking in AI search because it shapes the information environment models are trained and updated from.

A complete program includes three components: 1. Technical Foundations Ensuring crawlers (including GPT-indexers) can fully understand your website. 2. Model-Ready Content Bottom-of-funnel pages and narrative corrections that give AI engines accurate, sales-grade material. 3. Consensus Engineering High-authority off-site distribution across trusted domains to create category-wide consensus. This combination produces dominant AI search visibility and long-term defensibility.

Most clients see meaningful movement within 6–12 weeks, depending on: • competitiveness of category • clarity of existing narrative • volume of off-site signals • technical condition of the site • content depth and accuracy Reaching the #1 recommendation typically takes 3–6 months, with gains compounding as consensus spreads across domains. The earlier you start, the easier it is to secure and defend the position.

We track performance using: • AI recommendation share (how often your brand is suggested across prompts) • Position in LLM comparison queries • Frequency of branded vs. competitor mentions • Volume and quality of third-party citations • Growth in high-intent organic conversions • Reddit/community sentiment • Consensus signals across the web Instead of ranking positions, AI search success is measured by visibility, recommendation frequency and conversion impact.

Yes — when done properly. Our approach is: • distribution-based (not manipulative) • powered by real publishers and communities • aligned with Google's guidelines • focused on accuracy and quality • compliant with brand and legal requirements We never pursue tactics that would put your reputation, domain, or AI visibility at risk. Consensus engineering is about increasing clarity and trust, not exploiting loopholes.

Most high-growth companies invest between $5k–10k/month depending on: • category competitiveness • depth of content required • amount of off-site distribution • internal resources Series A–C is the ideal stage because: • your category definition is still flexible • competitors have not locked in AI dominance • narrative control gives a disproportionate advantage • the impact compounds quickly The earlier you optimise for AI search, the harder it becomes for competitors to dislodge your position.