Managed AI Search
Managed AI Search is an ongoing service that tracks how AI engines describe and cite your business, improves the pages and sources behind those answers, and measures the inquiries that follow. Schmitdy runs the research, content, outreach and reporting with your team in Slack, Teams or WhatsApp.

The shift
An AI answer can name a business, describe its offer and link to supporting sources before a buyer visits its website. Those are three separate opportunities to get the facts right. We check the questions that matter to your business, find missing or misleading evidence, and turn that research into work your team can approve.
Good SEO still matters. Google's guidance on AI features says existing SEO practices apply and no special AI schema is required. We improve access, useful content and supporting evidence. Engines decide what to include.
The daily loop
We track an agreed question set across ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews. Each read records the engine, date, question and cited sources. Daily checks guide the work; completed-week comparisons help us judge a trend. Missing answers and unavailable engine data are reported as gaps.

The question set, countries, languages and engines are agreed before measurement. When coverage changes, we mark the change so the comparison remains clear.
Want to test the sequence internally first? Open the full 90-day roadmap with inputs, owners and decision gates.
The four pillars
A versioned set of questions built from your sales conversations, search demand and category research, prioritized by commercial relevance.
The pages, threads, reviews, roundups, and creators the engines pull from for your category, and where the gaps are between you and the cited brands.
Approved pages, useful community contributions and editorial outreach with a record of what happened. Publication decisions remain with the editors and communities.
You're in our Slack, Teams, or WhatsApp, and we're in yours. Not a weekly status call.
Slack
Teams
WhatsApp
What we actually ship
AI agents handle the daily work. Expert human growth operators assess every claim, asset and placement before it ships.
We improve the pages that answer important buyer questions: clear claims, readable passages and evidence people can check. Structured data describes the visible offer. It does not replace useful content or guarantee a citation.

Some answers you'll never win with the pages you have, because the page doesn't exist yet. We build evergreen content engineered for citations, aimed at the exact gaps the daily read surfaces. You get it as a draft pack to review before anything goes live.
Slack
Teams
WhatsApp

We inspect the public threads and discussions cited in your category, then contribute where your team's expertise helps. We follow community rules and disclose relevant affiliations. Private groups and WhatsApp chats are collaboration spaces, not public sources we promise an engine can read.

We identify guides, comparisons and expert articles cited in the answers we sample for your category. We choose relevant publications from that source analysis and develop pitches that help their readers. Editors decide whether to publish.

AI engines fan a buyer question out into reviews, explainers and how-to searches. We turn the strongest video gaps into useful expert videos, then package each one so buyers and engines can find and understand it.
Works with you in
No weekly status call you forget to dial into. The team runs the channel from inside the tools you already live in. You see what's shipping, you ask for changes by message, and the daily signal lands where you'll actually read it.

What's included
Measurement
We agree the baseline, two monthly goals, sources, calculations and start and end dates in writing. Each measure answers a different question.
Before the baseline, the written method sets the runs per question and engine, how repeated answers are combined, and the country, language and available personalization controls. Each comparison reports its actual number of valid answers and any changed settings. Small samples can move by chance; unavailable controls and missing runs remain stated limitations.
Read the full AI Search measurement method, including share of voice, position, sentiment, accuracy, missing data and the difference between attribution and causation.
| Measure | What we count | What it tells you |
|---|---|---|
| Brand visibility | Valid sampled answers naming your brand, divided by all valid sampled answers in the agreed set. | How often you appear in that sample. It isn't total market share. |
| Website citations | Sampled answers linking to your website, with the exact cited URLs retained. | Whether your pages are used as sources. A brand mention doesn't require a citation. |
| Referred visits | Recorded site sessions with an identifiable AI referrer or campaign signal. | Trackable visits, not everyone who saw an AI answer. Lost referral data leaves a gap. |
| Qualified inquiries | Real business inquiries meeting the agreed fit criteria, with bookings and CRM status checked where connected. | Commercial progress. We distinguish direct referral evidence from self-reported or assisted discovery. |
Google includes AI-feature traffic within Search Console's Web reporting; it isn't a separate AI Overview conversion count. OpenAI documents ChatGPT referral tagging, which helps identify visits. Neither source makes visibility equivalent to revenue. Unavailable analytics or CRM data stays unmeasured.
Who it's for
FAQ
Works with your website stack
Squarespace
Vercel
Webflow
Shopify
HubSpot
Closing
You can keep finding out you're invisible from a sales rep who just lost a deal. Or you can have a senior team reading the engines every day and shipping against what they find, with half the fee riding on the result.