AI search optimization · Canada

AI Search Optimization

AI search optimization improves the pages and business information that AI-assisted search can discover and cite. We review crawl access, entity consistency, original evidence and answer quality, then track observable mentions and referrals with clear limits on what the data proves.

Vancouver-basedServing Canadian marketsClear scope and reporting

The work

A focused ai search optimization system

We connect search demand, technical quality, useful content and conversion paths. Every recommendation has a reason, an owner and a way to measure progress.

  • Brand and entity consistency
  • Crawlable, quotable answer resources
  • Topic and knowledge-gap mapping
  • Digital PR and reference opportunities
  • AI visibility observation and reporting

The signal

There is no single AI ranking switch. Strong source quality and a coherent brand footprint create a more durable foundation.

Search platforms build confidence from connected evidence. We strengthen the signals that matter to the query and remove contradictions that weaken relevance or trust.

Evidence standard

Use facts the business can support

Authority is strongest when it comes from accurate operations, real customer experience and relevant third-party recognition. We identify the proof required before a page, profile or outreach task is approved.

  • Consistent brand and entity information
  • Crawlable pages with explicit answers and sources
  • Recognizable expertise across trusted third-party references
  • Original material that adds information to the web

The sequence

Diagnose, prioritize, build, learn

We begin with the business model and search landscape, not a generic checklist. High-impact blockers come first; content and authority work follow a documented page and market plan.

  • Days 1–30: baseline, access, technical and profile blockers
  • Days 31–60: priority page, profile and conversion implementation
  • Days 61–90: reputation, citations, authority and content expansion
  • Ongoing: measure, learn and reprioritize

Measurement

Report the signals that lead to business outcomes

Rankings are useful context, not the final result. Reporting connects visibility with customer actions and qualified demand so the next decision is based on evidence.

  • Brand and service mention coverage in observed AI answers
  • Referral traffic from AI-assisted products
  • Source-page discovery and engagement
  • Qualified assisted conversions without invented attribution

Reviewed sources

Primary sources and standards

Use these official resources to confirm platform rules and technical guidance. They are maintained by their publishers and may change over time.

Useful answers

Questions before we start

Do I need llms.txt to appear in Google’s AI features?

Google says no additional special files or special schema are needed for its AI features. Crawlable, indexable pages and established SEO practices remain the foundation. An llms.txt file is not a ranking or citation guarantee.

Can you guarantee that ChatGPT or another AI system will recommend us?

No. Each system chooses its own sources and answers can vary. We improve the underlying source material and report observable mentions, citations and referral visits without promising placement.

What does an AI visibility check record?

A useful observation records the system, date, question, answer, cited URLs and whether a visit or enquiry could be measured. Repeated checks use comparable questions and retain the original evidence.