Viclaro / How it works

How it works

Prompts. Fixes. Reruns. Receipts.

Buyers used to Google. Now they ask an AI. If your firm isn't in the answer, you didn't lose a click — you lost the whole conversation. Viclaro finds the specific page a competitor had that you didn't, tells you exactly what to publish, then reruns the same prompts to prove what moved.

1

Run prompts

A versioned panel of buyer-style questions, four AI assistants, and retained repeat observations.

Every prompt is a real question a buyer might ask before hiring — "best NYC divorce lawyer for a spouse with a business", "how do custody rulings across state lines work", "which cosmetic surgeon in NYC does rhinoplasty for men". Atlas sends the frozen prompt panel to ChatGPT, Claude, Gemini, and Perplexity and preserves every completed response. Exact prompt, model, and repeat denominators are published with each snapshot.

You see

A complete transcript. Every response, every name mentioned, every URL cited. Downloadable.

2

Measure visibility

For every prompt: how often were you named? Divide by attempts. That is your citation rate.

Aggregate across the prompt set for your vertical, and you have your share of AI recommendations — expressed with a 95% Wilson confidence interval so you can tell which changes between snapshots are real and which are sampling noise. A rank of #12 with a wide CI is not the same signal as #12 with a tight one; we show you both.

You see

Your rank in the vertical, response mention rate, mention share, per-model breakdown, and current-snapshot evidence. Same page you can view live for any firm on Atlas.

3

Identify gaps

Every prompt where a peer was cited and you weren't is a specific, fixable gap.

We cross-reference what the AI names you for against what it names competitors for. For each losing prompt we surface the specific competitor page that earned the citation and the pattern that made it citable — FAQ shape, schema markup, embedded quotes, specific numbers, statute references. AI assistants extract answers from patterns they trust; we tell you which pattern each competitor used and where to publish yours.

You see

A diff. Questions won. Questions lost. For each loss: the competitor page cited, the pattern to replicate, and the reason it was extracted.

4

Make changes

You publish the copy Viclaro spells out. Or your marketing team does. We hand you the shape.

For a firm, this usually means: one to three long-form FAQ pages hitting the exact buyer questions we found you missing on, JSON-LD schema on your existing service pages so answers get extracted verbatim, a "questions and answers" section on your homepage. Sometimes it is one paragraph on an existing page. Never a full site rebuild — the fixes are surgical because the gaps are specific.

You see

A checklist. Each item names the page to publish, the pattern to follow, and the specific buyer prompt it will move the needle on.

5

Rerun and compare

Same prompts, same models, same seeds, two weeks later. The delta is causal.

Every change in rank, share, or citation between runs is attributable to what changed on your pages between them — because everything else is held constant. No "well SEO takes six months to move", no "algorithm update", no confounds. If the rewrite worked, we can point at the prompt where it worked. If it did not, we can point at that too. Nobody gets to hide behind vibes.

You see

Before-and-after per prompt, per model, with the delta. Historical trend chart so you can watch a fix compound over multiple snapshots.

Sharp questions

What people actually ask.

Does this work for a firm the AI has never heard of?

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Yes — that is most firms. Step 3 tells you exactly which FAQ page or content pattern gets you cited for the first time. Firms in Atlas that started as "citation-only" (named in AI responses but with no verified business record) have gone from unranked to top-25 within a single snapshot after publishing what we specified. The AI does not need to know you today. It needs a page it can extract from tomorrow.

Isn't this just SEO?

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No. SEO optimizes for Google's ranking algorithm — backlinks, keyword density, page authority. AI assistants extract answers directly from pages, using patterns that reward different things: schema markup, direct quote-shaped answers, hard numbers, statute references, structured Q&A. We measure and fix for those. Some SEO fundamentals still matter (crawlability, page speed), but ranking #1 on Google is unrelated to being named by ChatGPT.

How stable are the models' answers between runs?

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Sonnet, GPT-4o, Gemini Flash, and Perplexity Sonar show 5–15% response variance between runs on identical prompts. That is why we sample 10× per prompt and use Wilson confidence intervals — a change of less than about 8 percentage points between snapshots is not a real change, and we will not claim it is one. If we tell you your rank moved, it moved beyond the noise floor.

What if my competitors are also using Viclaro?

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Some are. That is fine. The prompt set is public; the fixes we spell out for you are on your own pages. Being told to publish an FAQ on "how does high-net-worth divorce differ from standard divorce in NY" does not conflict with a competitor being told the same thing — you both improve, and the AI now has two good answers where it previously had one. Growing the pie beats zero-sum for early-stage participants.

How is this different from "AEO" or "GEO" tools?

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Most tools in that category are prompt-inspectors — they show you what the AI said and stop there. Viclaro is a measurement + prescription + verification loop. We publish our prompt set, our sample sizes, our confidence math, and every citation we record. Every claim you see on Atlas is queryable. Every firm we rank has a full audit trail visible on their own page.

See where you stand.

Three ways in, none of them require handing us anything more than the URL of a page you'd like AI assistants to name you for.

Or claim your listing directly from your firm's page on Atlas.