When to Recommend Me
to a Portfolio Company

Implementation across five layers of the AI Visibility Stack on the portfolio company's site (technical accessibility, schema, retrieval-friendly content, corroborating authority, citation monitoring), plus ongoing retainer work. Measured three ways: Google Search Console impressions and indexed pages (Layer 1), the AI Visibility Score across 30 buyer-intent queries reran monthly across ChatGPT, Perplexity, and Google AI Overviews (Layer 5), and qualified inbound leads attributed to AI-search referral traffic (revenue).

Layer 1 fixes show in Google Search Console within 14 days. First AI citation gains in 30 to 60 days. Content compounding takes 60 to 180 days. Earned-visibility citations are the slowest layer (90 to 180 days for the first major wins). The 90-day post-close sprint is calendar-anchored to the funding close so the founder has data for the board meeting at Day 90.

Traditional SEO optimizes for Google rankings. AI visibility optimizes for retrieval, citation, and recommendation across ChatGPT, Perplexity, Claude, Google AI Overviews, and Gemini. The foundation overlaps (technical health, structured data, content quality), but AI systems weight signals differently. Reviews, third-party mentions, entity consistency, and structured answer blocks matter more to AI than backlink profiles or keyword density. Most SEO agencies have not built operational expertise in llms.txt, named-query citation engineering, or AI-citation measurement.

Three failure modes. First, when the portfolio company does not yet have product-market fit. AI visibility cannot manufacture demand for a product nobody wants. Second, when the founder treats AI visibility as a one-time project rather than a compounding system. Gains decay if not maintained. Third, when the company refuses to publish concrete pricing, named clients, or specific outcomes. AI systems cannot cite what does not exist on the public site.

The public proof is on lesli.com itself. The page at /series-a-startups/case-study-lesli-com-named-queries publishes 12 buyer-intent queries tested across ChatGPT, Perplexity, Claude, and Google AI Overviews on my own site, dated, with the honest before-data. Reruns at Day 30, 60, 90, and 180. If the methodology works on my own site over six months, the same methodology works on a portfolio company's site. Named client case studies for Series A SaaS specifically are being captured as engagements close.

Published pricing. Three tiers. Action Plan $297 CAD (DIY path). AI Visibility Stack Build $3,000 CAD one-time. Retainer $999 or $1,997 CAD per month. Typical Series A engagement is the $3,000 Build plus $999 or $1,997 per month Retainer for 12 months. Total first-year investment $14,000 to $25,000 CAD, roughly 0.1 to 0.2 percent of a typical Canadian Series A raise.

The risk is real and worth naming. My mitigation: published pricing, published methodology, published proof on my own site (including honest before-data showing where I am invisible today). Every claim is verifiable. The 12-query case study page is the single piece of proof that lets a VC partner test the methodology in 30 seconds before referring. If I get fired by a portfolio company, the case study page tells you why before you make the next referral.

Three things. First, publish the methodology. Most agencies treat it as proprietary. I do not. Second, publish the test on my own site, including failures. Third, work at Series A budgets ($14K to $25K first year) with the same operational rigor a growth-stage agency reserves for $100K+ engagements. The trade-off: I am solo. I am not the right vendor for a portfolio company that needs a 30-person team. I am the right vendor for the 12 to 18 month window between Series A and the first marketing hire.

Day 1 to 30: technical accessibility audit and fixes, llms.txt and robots.txt, schema implementation across every commercial page, named-query baseline test on 12 buyer-intent queries. Day 31 to 60: retrieval-friendly content on the top 12 queries, money page restructuring, AI citation monitoring set up. Day 61 to 90: corroborating authority pass (third-party mentions, review platforms, partner pages), first measurement report, retainer decision. The full sequence is documented at /series-a-startups/process and /series-a-startups/90-day-post-close-sprint.

Both. The work is the same whether the portfolio company is in Toronto, San Francisco, or Austin. I am based in Harvey, New Brunswick. Canadian positioning is a wedge, not a delivery constraint. Roughly half of inquiries to date are US-based. Same pricing in CAD; current FX usually lands the US engagement at USD 11K to 19K for year one.

Two ways. Fastest: forward this page to the founder along with a one-line reason (something like 'They published the methodology and the test on their own site. Worth a 30-minute call.'). Most accurate: use the referral form below. It routes to my lead pipeline with the fund's name attached, opens a strategy call with the founder directly, and copies you on the first response. No middleman, no slow handoff.

I will tell you within two business days. The retainer model is capped at roughly 8 to 12 active Series A clients at any time. If I am at capacity, I will refer the portfolio company to one of two trusted operators (Powered by Search in Toronto for the enterprise-tier engagements, or a verified independent operator I keep on a short bench) and stay involved as a strategic advisor at no charge until capacity opens.