Synergy Homes
A website and inquiry intake for a Winnipeg custom home builder
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AI Search Optimization be described accurately in AI answers
Clear facts, structure and content that make your business easier for AI assistants to understand. The platforms decide what they show.
At a glance
- Entity and knowledge graph work
- schema.org depth
- Crawlable, quotable pages
- AI answer share monitoring
- We build the same kind of retrieval systems we optimise for
What a typical engagement includes
- An AI visibility baseline: a prompt set built from the questions your buyers genuinely ask, run across the major assistants and AI Overviews, logging who gets cited, what gets said about you, and where competitors are named instead
- An entity and knowledge graph audit covering name, address, founding, leadership, services and description across every source a model can reach
- Structured data built or repaired: Organization, Service, FAQPage, Article, Person and Product, connected with @id and sameAs so the graph resolves as one entity
- A deliberate AI crawler policy: which assistants may read the site and which are kept out. We can add an llms.txt file as well, but it is an unofficial convention that few assistants are known to read, so we treat it as a small extra, not a lever
- Content rebuilt to be citable: a direct answer near the top, defined terms, dated and attributable claims, named authors, first hand experience instead of paraphrased consensus
- A source consistency pass across directories, professional profiles, review platforms and press, so corroboration works in your favour
- Monitoring: recurring prompt runs tracking answer share, citation counts and sentiment inside answers, reported on a cadence you choose
AI search optimization, in detail
Help ChatGPT, Gemini, Perplexity and Google AI Overviews describe your business accurately: entity work, structured data, crawlable pages and answer tracking.
Search used to end in a click. Increasingly it ends in a paragraph: ChatGPT answers, Gemini summarises, Perplexity cites three sources, and Google writes an AI Overview above the results. Your rankings can hold steady while your sessions fall, because the answer got assembled somewhere you have no analytics on. Nothing broke. The interface moved.
AI Search Optimization, often called Generative Engine Optimization, is the work of becoming one of the sources that answer is assembled from, and of shaping what gets said about you when it is. The assistants decide what they cite, so nobody can guarantee a mention. What we can do is make the facts about you accurate, consistent and easy for them to read, and measure what changes.
What AI search optimization means in our hands
We build the same kind of retrieval systems we optimise for. Redenn builds RAG pipelines, embeddings, rerankers and evaluation harnesses, and runs its own AI chatbot in production. We know how a passage actually gets selected: it has to be retrievable, self contained, unambiguous about who is making the claim, and corroborated elsewhere. That is an engineering view of the problem. See /services/llm-development for the other side of the same coin.
Entity first, keywords second. A model does not rank you, it resolves you. Before anything cites you it has to know the business exists, what category it sits in, who runs it, where it operates and what it sells. We treat your entity as the deliverable: a linked schema graph on your own domain, consistent naming and description across every profile and mention, and clean signals for the knowledge panel.
Machine readable by construction. AI crawlers are less forgiving than Googlebot. Content that only appears after JavaScript runs, or hides behind an accordion, often is not there at all as far as retrieval is concerned. We serve clean, server rendered HTML with real semantic structure, and we verify it rather than assume it.
The stack and the approach
- Delivery: Next.js 16, server rendered, fast on a real phone (we measure it before launch), built to WCAG 2.1 AA as our accessibility target. Retrievability, speed and accessibility are the same problem wearing different hats.
- Markup: hand written JSON-LD graphs rather than plugin output, validated and version controlled with the rest of the site.
- Measurement: a harness we set up to run your prompt set against model APIs on a schedule, so change over time is evidence rather than anecdote.
- Foundations: classic search discipline underneath, because assistants retrieve from the indexed web. This sits on top of SEO, never instead of it.
What this looks like in practice
Two typical engagement shapes.
A GEO layer on an existing site. A business that still ranks respectably but has stopped appearing inside AI answers. We baseline the prompt set, repair the entity and schema graph, rewrite the highest value pages to be quotable, tidy the off site sources, then stand up monitoring and hand it over.
Build and GEO together. A rebuild where information architecture, schema graph and content model are designed for retrieval from the first wireframe rather than retrofitted later. This pairs with /services/web-design, and ongoing monitoring can fold into a Care Plan.
Pricing
Scoped per project. The cost depends on how many locations you carry, how far your markup and off site sources have drifted, and how much content needs rebuilding. You get a fixed price after a scoping call. Contact us for a quote, or send a URL through the free audit first.
Planning the work
Make the business easier to understand, verify and cite.
What to cover in the scope
- Answer specific buying questions in clear, crawlable page content.
- Keep company, service, author and location information consistent.
- Support important claims with original examples, evidence and accurate structured data.
What helps us plan
Bring your strongest service knowledge, real project information and the questions prospects use when comparing providers. Identify claims that still need evidence before they are published.
How to judge the result
Observe citations and relevant referral traffic where measurable, alongside ordinary search and inquiries. AI answers vary by query and platform; inclusion or recommendation cannot be promised.
From your first message to every month after.
Tell us what to fix
A few lines on the form, or ask the assistant. A person replies within 4 business hours.
A call, then your plan
What to fix first and why, what we'd build and run, the price and the go-live date, in writing within two business days.
We build and launch
A website takes 2 to 6 weeks, a web app 8 to 16. Tested on real phones before launch.
We run it, every month
Hosting, updates and the systems kept working. Monthly plans cancel any time.
Straight answers before you sign
You own everything.
Your code, your domain, your accounts and your data.
One contract, your currency.
You sign with Redenn Informatics Pvt. Ltd. (India) and are invoiced in your own currency. North American work is led from our Brampton, Ontario office (Redenn Informatics Inc.).
Tested on real phones.
Built mobile-first, load time measured before launch, designed to WCAG 2.1 AA.
Prices published.
Websites from $1,200, web apps from $15,000, monthly systems $149 to $249/mo plus setup from $500, and care from $49/mo.
Quoted and invoiced in your own currency by Redenn Informatics Pvt. Ltd. (India); pay by card through Razorpay or by bank transfer.
Questions about AI search optimization
Traditional SEO earns you a position on a results page. AI search optimization, sometimes called generative engine optimization, earns you a place inside the answer itself when someone asks ChatGPT, Gemini, Perplexity or Google AI Overviews a buying question. The work is genuinely different: assistants care less about keywords and more about whether your business resolves as a clear entity, whether your pages are machine-readable by construction, and whether your claims are specific enough to cite. Existing SEO is a foundation, not a substitute; a site can do fine in classic Google results and still be invisible in AI answers.
No, and nobody honest can, because the assistants decide what they cite and their behaviour keeps changing. What we control is everything that makes citation more likely: server-rendered pages with semantic structure, a consistent entity across directories and professional profiles, hand-written JSON-LD schema, an llms.txt file with a deliberate AI crawler policy, and content rebuilt so a direct answer sits near the top with dated, attributable claims. Then we measure instead of guessing: recurring prompt runs track your answer share, citation counts and sentiment over time, so you see movement, or the honest lack of it, in real numbers.
Both engagements exist, and the scoping call decides which fits. The GEO layer is applied to a site that already ranks respectably but never appears in AI answers: we repair structured data, entity consistency, crawler policy and content citability on what you have, then establish monitoring. The full build pairs with our web design work and integrates retrieval into the information architecture from the wireframe stage onward, which is the right call when the current site is due for replacement anyway. Because we build retrieval systems ourselves, including RAG pipelines, embeddings and rerankers, we optimise for how those systems actually read pages.
Tell us where you want to be found. We'll write the plan.
A person replies within 4 business hours. Your written growth plan follows within two business days.
Or call +1 437 524 3001 or toll-free +1 888 905 4003, or email hello@redenn.com.