Buyers don't search anymore — they ask ChatGPT, Gemini and Perplexity. Euclis gets businesses into the answer, and proves it with before-and-after.
This is the 2005 "you're not on Google" moment, repeating at 10× speed — except this time, every business owner already uses ChatGPT and believes instantly.
This is the demo. We run the exact question their buyers ask — live, in front of them. A competitor is recommended by name. They are not mentioned at all.
Nobody needs this explained twice. They ask one thing back: "How do I get in there?" — and that question is our product.
Peec ($29M raised), Profound, Otterly, HubSpot AEO, Semrush — scores, charts, and a weekly email confirming you're still invisible. The average dedicated tool already costs $337/month… to watch.
The customer's question was never "what's my score?" It's "make me the answer." Structured pages AI can quote, the sources AI actually cites, week-over-week proof of movement. That layer is open.
Monitoring is a feature. The outcome is the product. Every dollar incumbents spend educating the market about the problem is free demand generation for the company that solves it.
Enter a website. Euclis generates the 50 questions that business's buyers actually ask, runs them across ChatGPT, Gemini, Perplexity and AI Overviews — and shows who wins each answer, and which sources the AI cited to decide.
A prioritized, largely auto-executed plan: answer-formatted pages and schema AI can quote, llms.txt, entity cleanup — plus the exact Reddit threads, listicles and directories the engines cite in that niche, with drafted pitches to get into them.
Prompts re-run weekly. Before/after screenshots of real AI answers: "Two weeks ago you were absent. Today Perplexity recommends you for 6 of 20 buyer questions." Canceling means going dark again.
Agencies scan their whole client book, send Euclis-generated branded reports and fix plans, and resell "AI visibility" at $300–500 per client per month. We're the back office of a brand-new service line.
Every free scan ends with the same fork: fix it yourself with our plan — or press one button and let Euclis do it. Either way, the report gets forwarded. Every scan is a customer or a referral.
Peec raised $29M; HubSpot, Semrush and Ahrefs all shipped AEO products this cycle. The market already pays $337/mo on average — for monitoring alone.
AI citation patterns are legible today — Reddit, review sites, structured pages — and influenceable by small brands. Early-SEO-era leverage, briefly available again.
Every model release reshuffles the answers. Like Google updates fed SEO for 20 years, answer volatility makes this a forever-recurring product.
Price benchmarks already exist: agencies pay $189–795/month for monitoring alone. A product that includes the fix earns those prices with a much stronger claim.
AI Visibility Scan — brutal, shareable, rate-limited. Every scan is a lead or a referral artifact.
1 business · weekly tracking, 25 prompts, 3 engines · fix plan + on-site drafts.
100 prompts, all engines · off-site citation targeting with drafted outreach · CMS push · proof-loop reports.
10 client slots, full white-label, pitch-mode scans · $15 per extra client. Undercuts the $245+ incumbent floor — while including fixes.
Later: done-for-you execution at $500+/brand/month — productized-service margin on top of software. Agencies resell us at $300–500/client, so our fee is a fraction of their new revenue.
| Who | What they sell | Why they don't own our lane |
|---|---|---|
| Profound · $99–399+ | Enterprise AEO monitoring, citation intel | Fortune-500 focus; multi-engine starts at $399; monitoring-first. |
| Peec · $95–795 · $29M raised | Multi-market visibility analytics | No white-label on published tiers; analytics, not action. |
| Otterly, GEO Grader, Rank Prompt · $29–189 | Budget monitoring + agency reports | Reports about the problem — the client still asks "so what do we DO?" |
| HubSpot / Semrush / Ahrefs · $50–398 add-ons | AEO bolted onto SEO suites | Category validation; generic advice, suite lock-in, no service motion. |
Compounding moat: a cross-niche dataset of which fixes actually move AI answers — the one thing a mirror can never learn, because mirrors don't act.
20 hand-made scans for real businesses and agencies. Gate: 8+ ask "how do I fix this?" — validation, sales call and training data in one.
Self-serve scan: buyer-prompt generation → multi-engine runs → visibility report with cited-source breakdown. Gate: 500 scans, 10%+ request the fix plan.
Fix plans, on-site drafts, weekly proof loop, Stripe, agency white-label beta. Gate: 20 paying customers incl. 5 agencies.
Citation targeting, CMS integrations, public agency program. $10K+ MRR, 40% from agencies → pre-seed + YC with global revenue.
Kill criterion is pre-committed: if fewer than 5% of 500 free scans convert to fix-plan interest, the pain is voyeuristic — we re-cut the wedge with the data in hand.
B.Tech CS, full-stack engineer for years. Owns prompt-run infrastructure, multi-engine orchestration, report and draft generation, per-scan cost control, CMS integrations.
B.Tech. Owns concierge scans, agency channel, gut-punch content engine, pricing and fundraising. Operating metric: 20+ scans delivered to real prospects every week.
The product is prompt-running, analysis and content generation — squarely inside our stack. We eat our own cooking publicly: Euclis's own content is built to be cited by AI engines, and the receipts are public.
Raising to reach $10K+ MRR with 40% from agency white-label, harden the scan-and-fix pipeline, and win the SMB action layer before the monitoring crowd pivots. Student-founder capital first — Campus Fund, gradCapital, 100X.VC, Antler — then YC with global revenue in hand.