The post-search optimization stack.
Three connected disciplines that work together to make your brand the chosen answer - across every AI surface that matters.
Answer Engine Optimization
Voice assistants, AI overviews, and chat-first interfaces don't show ten links - they show one answer. AEO is the discipline of becoming that answer.
We restructure your content into atomic, citable units. We tighten claims, add evidence, and rewrite for the way AI assistants extract - so when a user asks the question, the assistant returns your sentence.
- Question-intent mapping for every page
- Answer-first restructuring + atomic snippets
- Schema markup tuned for assistants (FAQ, HowTo, QA)
- Voice-readability rewrites
Generative Engine Optimization
Generative search engines - Perplexity, Gemini, ChatGPT search, Copilot - synthesize answers from many sources. GEO maximizes the chance one of them is yours.
We engineer your content to be ingested cleanly: clear sectioning, defensible claims, original data, and the structural cues retrieval systems reward. Then we monitor share-of-answer week over week.
- Retrieval-friendly architecture
- Original data and primary-source positioning
- Citation-bait formatting (lists, tables, definitions)
- Continuous prompt-corpus tracking
Large Language Model Optimization
Long after you publish, your content lives inside model training data. LLMO is how you make sure the meaning models absorb is the meaning you intended.
We work at the entity layer: disambiguating your brand, resolving knowledge graph conflicts, building the corpus signals that determine how models think about you when no link is involved.
- Entity disambiguation across major knowledge graphs
- Authority anchoring on co-cited domains
- Structured fact-bundles for model ingestion
- Brand-narrative consistency at scale
Audit. Refine. Monitor.
Every engagement runs the same loop - calibrated to your category, scale, and stack.
What you actually get.
- Multi-surface AI visibility audit (5+ assistants, 200+ prompts)
- Atomic content restructuring with answer-first templates
- Schema & structured-data implementation (JSON-LD)
- Entity & knowledge-graph alignment
- Prompt-query corpus built for your category
- Citation outreach & co-mention strategy
- Weekly share-of-answer monitoring dashboard
- Quarterly model-drift recalibration
- Voice-assistant transcript optimization
- Internal stakeholder reporting + readouts
The questions everyone asks first.
How is this different from SEO?
SEO optimizes for ranking in a list of links. AEO optimizes for being the answer when the list disappears. Different signals, different formats, different success metric: share-of-answer instead of share-of-clicks.
Do I have to abandon SEO?
No. The two reinforce each other - clean schema, fast pages, and crawlable architecture help both. We layer AEO on top of healthy SEO foundations.
How long until we see results?
Citation lift typically appears within 30 days for newer surfaces (Perplexity) and 60–90 days for retrained models (ChatGPT, Gemini). We send a baseline report at week 2 so you can track week-over-week.
Which AI surfaces do you cover?
ChatGPT, Perplexity, Gemini, Claude, Copilot, Google AI Overviews, and voice assistants (Alexa, Siri, Google Assistant). Enterprise plans include private LLM deployments.
What if a model retrains and we lose visibility?
That's exactly why we monitor weekly. Model drift is part of the territory - our job is to detect it early and recalibrate before it costs you traffic.
Ready to be the answer?
Start with a free 14-day visibility audit across every major AI surface.