Visiby AI Search Visibility

What is it

Visiby AI Search Visibility is a monitoring and optimization tool for the emerging discipline of AI search optimization — sometimes called AEO (Answer Engine Optimization) or GEO (Generative Engine Optimization). In plain English: instead of tracking where your brand ranks on Google's ten blue links, Visiby tracks how often ChatGPT, Perplexity, Gemini, Claude, and Google's AI Overviews mention, cite, or recommend your brand when users ask relevant questions.

The technical essence is a prompt-monitoring engine. You feed it a set of buyer-intent questions ("best CRM for solo founders," "alternatives to Notion"), it runs those prompts across multiple LLMs on a schedule, and it logs whether your brand appears, in what position, with what sentiment, and which competitors got cited instead. The business significance is bigger than the tool itself: AI assistants are becoming the first stop for purchase research, and almost no brand has any visibility into that channel. Visiby is one of the first movers trying to own the measurement layer of a category that barely existed 18 months ago.

Why now

Three things converged to make this category viable in late 2025 and 2026. First, consumer behavior shifted. ChatGPT passed 800 million weekly active users, and Perplexity crossed roughly 30 million monthly actives. A meaningful slice of product research that used to start on Google now starts inside a chat window. Second, AI Overviews rolled out broadly in Google Search, meaning even traditional SEO traffic is now mediated by an LLM summary that cites a handful of sources — often not the ones ranking #1.

Third, and most important for indie developers: the measurement gap became obvious. SEO has Ahrefs, Semrush, and Moz. AI search has almost nothing mature. Brands started asking "why did ChatGPT recommend my competitor and not me?" and nobody had a clean dashboard answer. That question is the wedge.

This wasn't viable a year earlier because LLM answers were too inconsistent and API costs too high to run thousands of scheduled prompts cheaply. It won't wait another year because the incumbents — Semrush, Ahrefs, and likely HubSpot — are already shipping AI visibility modules. The window for a focused indie tool is roughly the next 12–18 months.

Market Evidence

The raw signals are thin but directionally interesting. Visiby shows up across 2 independent sources (Product Hunt and Google News) with 2 total mentions and a 100% growth rate from a nascent base. A 100% growth rate on a base of 2 mentions is statistically meaningless — it just means the term went from 1 mention to 2. The trend score of 65/100 is moderate, and the opportunity, market, demand, competition, and SEO difficulty scores all sit at 0/100, which in this dataset means "not yet measured," not "no opportunity."

My read: this is a real category with a weak specific signal. The category (AI search optimization) is genuinely hot — you can see it in the flood of "GEO" and "AEO" content marketing, in Semrush launching an AI visibility toolkit, and in Profound raising serious venture money. But Visiby the specific product is not yet a proven winner. Treat the term as a category signal, not a company signal. The demand is real; the brand is unproven. That's actually good news for a builder — you're not late to a validated winner, you're early to a validated category.

Who's Behind It

The category is being driven by a mix of scrappy startups and incumbent SEO platforms. The most-funded pure-play is Profound (raised around $3.5M seed, backed by Khosla Ventures), which sells AI visibility tracking to enterprise brands. On the indie side you have tools like Peec AI, Otterly.ai, and Scrunch AI, all launched in 2024–2025. Visiby itself appears to be an early-stage, low-profile entrant — no major funding signal, no dominant founder narrative yet.

The "whales" to watch are the incumbents: Semrush shipped an AI Toolkit, Ahrefs has been publishing heavily on AI search, and HubSpot's AEO Grader is a free lead magnet. These companies have distribution and existing SEO customer bases. Their weakness is focus — AI visibility is a feature to them, not the product. That's the classic indie opening: be 10x better at the one thing the incumbent treats as a checkbox.

TAM & Market Size

The buyer is anyone whose revenue depends on being discovered online: SEO managers, content marketers, growth leads, and increasingly founders at B2B SaaS and DTC brands. The realistic serviceable market is the overlap of two groups — companies already paying for SEO tools (roughly 5–8 million globally, per Semrush's own disclosures) and companies that care about AI citation. Today that overlap is small, maybe 50,000–150,000 teams actively searching for an AI visibility solution, but it's growing fast.

Price tolerance is the key question. SEO tools anchor at $99–$999/month for prosumer and SMB tiers. AI visibility tools currently price higher because they're novel: Profound starts around $499/month, Otterly around $29–$99/month, Peec AI around $90/month. That spread tells you the market hasn't settled. For a new entrant, $49–$199/month is the sweet spot: cheap enough for indie founders and small agencies to swipe a card, expensive enough to fund API costs.

The 0/100 demand score here reflects unmeasured data, not zero demand. I'd treat the real addressable demand as "small but real and compounding." Will they pay? Yes — the ones who already pay for SEO tools will pay for a second dashboard that answers a question their current tools can't.

Competitive Landscape

The field splits into three tiers. Enterprise: Profound, Scrunch AI — expensive, sales-led, focused on big brands and agencies. Mid-market/indie: Peec AI, Otterly.ai, AIclicks — self-serve, $29–$200/month, prompt tracking plus basic recommendations. Incumbent bolt-ons: Semrush AI Toolkit, Ahrefs, HubSpot AEO Grader — bundled, shallow, but free or already-paid-for.

Gaps worth attacking: (1) Most tools only measure — they tell you your visibility score but give weak, generic advice on how to improve it. The "how do I actually get cited" workflow is underserved. (2) Almost nobody does vertical-specific tracking well — e.g., "best project management tool for agencies" vs. generic software prompts. (3) Local and non-English AI search is essentially untouched. (4) Competitor citation analysis — showing exactly which sources an LLM pulled from and how to get into those sources — is a strong differentiator.

Big Tech entry risk: Google and OpenAI could expose native citation analytics. Google already shows some of this in Search Console. If they ship it free, the measurement layer commoditizes. But they won't ship the cross-platform view (across ChatGPT + Perplexity + Gemini + Claude) or the improvement playbooks. That's your defensible slice. You have roughly 12–18 months before this gets crowded.

Business Model

Subscription SaaS is the right model — this is a recurring monitoring job with recurring API costs, so one-time pricing makes no sense and freemium will bleed you on LLM API spend. The natural structure is tiered by number of tracked prompts and platforms.

Suggested pricing:

• Starter — $49/month: 50 tracked prompts, 3 AI platforms, weekly refresh, 1 user.
• Growth — $149/month: 250 prompts, 5 platforms, daily refresh, competitor tracking, 3 users.
• Agency — $399/month: 1,000 prompts, white-label reports, unlimited users, API access.

These numbers are anchored to Otterly ($29–$99) at the low end and Profound ($499+) at the high end, leaving a clear middle. The Agency tier matters most — agencies resell this to clients and tolerate higher prices for white-labeling.

12-month revenue forecast (assuming a solo founder or two-person team):

• Conservative: 40 paying customers, avg $90/mo → ~$43K ARR.
• Base: 120 customers, avg $110/mo → ~$158K ARR.
• Optimistic: 350 customers, avg $130/mo → ~$546K ARR.

CAC estimate: $80–$250 via content marketing and Product Hunt, higher ($400+) if you touch paid ads. Payback period of 2–4 months at the $99–$149 tier is healthy. Keep gross margin above 70% by caching LLM responses and limiting refresh frequency on lower tiers.

MVP Blueprint

Build the smallest thing that answers one question: "When someone asks an AI about my category, does my brand show up?" Cut everything else.

Core features (only these):

1. User enters 10–50 prompts (or picks from templates).
2. Backend runs each prompt against 3 platforms — ChatGPT (via API), Perplexity (via API), and Gemini (via API) — on a daily or weekly cron.
3. Parse each response for brand mentions, competitor mentions, and cited source URLs.
4. One dashboard: visibility score over time, mention rate per platform, competitor comparison table, and a list of sources the AI cited.
5. Email digest.

Explicitly cut for v1: sentiment analysis, recommendation engine, white-labeling, team seats, Slack integration, historical backfill beyond 30 days.

Tech stack: Next.js + Tailwind for the front end, Supabase (Postgres + auth) for data, a Node or Python worker on a cron (Railway, Fly.io, or Vercel Cron) to run prompts, OpenAI + Perplexity + Google AI APIs for the queries. Store raw responses as JSON so you can re-analyze later without re-querying.

Fastest path to launch: build the prompt-runner as a script first, prove the data is useful in a spreadsheet, then wrap it in a UI. Realistic build time for a competent solo dev is 5–7 days if you resist scope creep. Ship to Product Hunt and a few SEO Slack communities. Suggested product types here are SaaS, Tool, and API — start with SaaS, expose the API later once agencies ask for it.

Commercial Opportunities

1. Agency white-label dashboard. Target: boutique SEO and content agencies (10–50 clients). They need to show clients "here's your AI visibility" in a branded report. Expected revenue: $300–$800/month per agency, 20–40 agencies within a year → $6K–$32K MRR. This beats chasing individual brands because agencies have many clients and high retention.

2. Vertical-specific AEO tracker. Target: one niche, e.g., legal, healthcare, or B2B SaaS. Generic tools can't answer "which law firms does ChatGPT recommend in Austin?" A vertical tool can. Revenue: $99–$299/month, higher willingness to pay because the stakes are higher. Beats horizontal because you can win a niche before incumbents bother.

3. "Get cited" playbook + tool combo. Target: content marketers who know their score is bad but don't know why. Sell the diagnosis (tracker) plus the fix (which sources to pitch, what content structure LLMs prefer). Revenue: $79–$199/month, or a $500 one-time audit. Beats pure tracking tools because measurement alone is a race to the bottom on price.

Product Ideas

🥇 CiteWatch — "Know which sources AI cites in your niche." One-line value prop: track not just whether you're mentioned, but exactly which URLs the LLM pulled from, so you know where to earn a citation. Target user: content marketers and SEO leads at B2B SaaS. Why now: everyone tracks mentions; almost nobody tracks the sources, which is the actionable layer. This is the clearest differentiation and the easiest to explain.

🥈 AEO Grader — free lead-gen tool. One-line value prop: enter your domain, get a free AI visibility score across ChatGPT and Perplexity in 60 seconds. Target user: anyone curious, top-of-funnel. Why now: HubSpot proved the free-grader playbook works; there's no dominant free AEO grader yet. Monetize with a paid tier for ongoing tracking.

🥉 Vertical AEO Tracker — pick one industry. One-line value prop: the AI visibility dashboard built specifically for [legal / dental / SaaS]. Target user: niche agencies and multi-location businesses. Why now: horizontal tools are generic; vertical depth wins loyalty and commands higher prices. Slower to scale but defensible.

Priority order: start with CiteWatch because it's the sharpest wedge and fastest to validate. Use AEO Grader as the acquisition engine. Add vertical later once you see which niche converts best.

SEO Opportunity

Search interest in "AI search optimization," "GEO," and "AEO" is climbing steeply from a small base — classic early-category curve. SEO difficulty is scored 0/100 here, meaning the SERPs are not yet locked up by big domains. Long-tail keywords worth targeting: "how to rank in ChatGPT," "AI overviews tracking tool," "Perplexity brand monitoring," "generative engine optimization tools," "track brand mentions in AI search." Competition is thin on all of these today.

Content strategy tip: write comparison and "how to" pages now while the terms are uncontested — "Otterly vs Profound vs [your tool]," "how to get cited by ChatGPT." These rank fast in an emerging category and convert because the intent is commercial. Move within 6 months before Semrush's content machine owns the SERP.

Risk Assessment

Risk 1 — Platform commoditization. Google or OpenAI ship native citation analytics for free. Likelihood: medium. Mitigation: own the cross-platform view and the improvement workflow, not just the raw data.

Risk 2 — LLM API cost and instability. Running thousands of prompts daily gets expensive, and providers change pricing or rate limits. Likelihood: high. Mitigation: cache aggressively, cap prompts per tier, and negotiate volume pricing early.

Risk 3 — Category confusion. "AEO," "GEO," "AI visibility" — buyers may not know what to search for, so demand stays latent longer than expected. Likelihood: medium-high. Mitigation: lead with outcomes ("find out if ChatGPT recommends you"), not jargon.

How to validate cheaply: before writing a line of code, manually run 50 prompts for 10 target brands in a spreadsheet, show the results to 5 potential buyers, and ask if they'd pay $99/month. If 3 say yes, build. When to walk away: if incumbents ship free cross-platform tracking before you launch, or if your manual validation gets zero willingness-to-pay, kill it and keep the prompt list as content.

Action Plan

Today: pick 10 brands in one niche you understand, manually run 30–50 buyer-intent prompts across ChatGPT, Perplexity, and Gemini, and log mentions in a spreadsheet. This costs you a few hours and zero dollars.

This week: turn that spreadsheet into a one-page "AI visibility report" for one of those brands. Send it cold to 10 marketing leads. Ask: "Would you pay $99/month for this every week?" Track replies.

Week 1 goal: 10 outreach messages sent, at least 3 conversations started, 1 clear willingness-to-pay signal.

Month 1 goal: if signal confirms, build the MVP from the blueprint above and get 5 beta users running it free in exchange for feedback. Ship a landing page with the free AEO Grader to start collecting emails.

Month 3 goal: convert 10–20 beta users to paid at $49–$149/month, publish 5 SEO comparison pages, and launch on Product Hunt. If you have under 5 paying customers by month 3, revisit pricing or pivot the wedge toward the agency white-label opportunity.

Related Terms

Generative Engine Optimization (GEO) — the umbrella discipline Visiby operates in; optimizing content so LLMs cite it. Answer Engine Optimization (AEO) — the closely related practice focused on featured snippets and AI answers. LLM SEO / AI SEO — the broader search term buyers actually use, which is your best SEO entry point. All three describe the same shift Visiby monetizes: discovery is moving from ranked links to generated answers, and the tools to measure that shift are still being built.