CLICON | We Quantify Your Revenue at Risk from LLMs

CLICON LOTUS

GEO Intelligence Engine

We quantify what you're losing.

We generate the code to recover it.

Request Demo How it works →

Also available from Claude, Cursor, and any MCP-compatible AI assistant. How to connect →

Live

GPTBot · PerplexityBot · GoogleBot-AI · ClaudeBot · Amazonbot — monitored

Citation drop −23% · PerplexityBot — 11 min ago

ClaudeBot crawl completed on competitor.io — 18 min ago

New competitor detected: rival-agency.com

GEO code auto-generated — countering rival movement

GPTBot visits your site in ~11 days — code ready

ROI at risk: $48,200 USD — Q2 2026

EVIDENCE · LATAM B2B

The shift already happened.
The numbers are just showing up.

01 · CTR

61%

Drop in organic CTR since AI Overviews.

Fuel Online · 2026

02 · CLICK-THROUGH

Of users click links inside AI answers.

Pew Research · 2025

03 · VISIBILITY

62%

Of brands are invisible to AI models.

Fuel Online · 2026

04 · MARKET 2028

$750B

In sales via generative engines by 2028.

McKinsey

$100M+ already invested in GEO tools globally.

Zero operate in LATAM. Zero in Spanish.

PROPRIETARY MECHANISM · BLEED MODEL

We don't tell you you're losing traffic.
We tell you how much it's costing you.

The Bleed Model is the financial model that converts your AI search visibility loss into quantified revenue. We cross your historical organic traffic, AI bot behavior on your site, citations you're losing in LLMs, and your unit conversion value. The result is a USD figure your CFO can audit.

Other tools measure Share of Voice. Lotus measures what it costs you to not have it.

INPUTS

01Verified historical organic traffic via Search Console.

02Visit frequency and pattern from GPTBot, ClaudeBot, PerplexityBot.

03Citation gap measured against competitors in AI responses.

04Declared or inferred conversion value from your site.

OUTPUT

Revenue at risk in USD, monthly, with biweekly versioned history.

01 // Diagnostics

The market doesn't see
what Lotus sees.

Proprietary data no competitor can replicate. Real intelligence, not dashboards.

All AI bots monitoredGPTBot, PerplexityBot, GoogleBot-AI, ClaudeBot, Amazonbot and more. Frequency, timing and what they find in your market.

Competitor hash diffEvery change on your competitor's site, versioned and automatically notified.

ROI EngineExact financial Business Impact with the Bleed Model 2026. No estimates.

GEO code auto-generatedLotus generates the exact code to counter your competitor's moves and maintain your relevance to LLMs before their next bot visit.

Full autonomyBiweekly scheduler, event triggers and artifact auto-regeneration. Zero intervention.

MCP

Lotus in your IDE and chatCall Lotus from Claude, Cursor, VS Code, or any MCP client. Analysis, quick wins, and competitive actions without leaving your workflow. How to connect →

OPERATION · AUTONOMOUS CYCLE

Four steps.
No manual intervention between cycles.

// Detect

All bots

We monitor GPTBot, ClaudeBot, PerplexityBot, GoogleBot-AI and Amazonbot on your site. Visit frequency, timing, which pages they read and what they took.

// Analyze

We cross the data

We cross your Search Console data with versioned scraping of your competitors and the diff of changes between cycles. We detect what they're copying from you and where they're leaving you behind.

// Quantify

Revenue at risk

The Bleed Model calculates your revenue at risk in USD, with month-over-month history and projection for the next cycle.

// Generate

GEO Code

We produce GEO artifacts ready to deploy: llms.txt, JSON-LD (product, offers, organization), structured data and hreflang. Code, not recommendations.

Lotus runs on a biweekly or weekly scheduler. When a competitor changes something critical, Lotus also fires off-cycle. You don't touch anything.

03 // Arsenal

What the market
can't replicate.

$ lotus analyze --domain clicon.app --competitors 3
[✓] Crawl frequency detected: GPTBot every 11 days
[✓] 3 competitors scanned — hash diff complete
[✓] Citation gap identified: 23% drop in Q1 2026
[✓] Bleed Model calculated: $304,500/mo at risk
Generating GEO defense artifacts...
→ llms.txt ...............READY
→ JSON-LD (product) ......READY
→ JSON-LD (offers) .......READY
→ Structured data ........READY
[✓] Artifacts generated — awaiting deployment approval
[✓] Next GPTBot visit: ~11 days — defense active

DATA

✕Third-party metric dashboards

✓Direct LLM citation measurement — proprietary data no one else has

COMPETITION

✕Static keyword reports

✓Real-time hash diff: every change on your competitor's site, detected and versioned

OUTPUT

✕Generic PDF recommendations

✓Executable GEO code: llms.txt, JSON-LD, structured data — ready to deploy

AUTOMATION

✕Periodic manual analysis

✓Autonomous scheduler with triggers: citation drop, new competitor, content change

ROI

✕"Your organic traffic dropped X%"

✓Exact revenue at risk — numbers a CFO can audit

Accuracy crawl prediction

Faster than manual analysis

Hours to first report

Non-replicable data

PLANS · MONTHLY USD

Pro, Growth, Agency.
Same engine. Different operation.

No annual discount. No lock-in. Cancel anytime.

PRO

Desde $399/mo

Monitored domains1

Competitors per domain3

Analysis frequencyBiweekly

Users1

Bleed Model report✓

Dashboard + API key✓

Request access

GROWTH

Monitored domains1

Competitors per domain5

Analysis frequencyWeekly

Users3

Priority triggers✓

Direct founder support✓

Request access

For agencies

AGENCY

WHITE LABEL

Your brand, our intelligence. Agency-branded dashboard, white label PDF reports, and client management panel.

Monitored domains5

Competitors per domain5

Analysis frequencyWeekly

Users10

Client-branded PDFs✓

Full dashboard access✓

Agency-level support✓

Talk to sales

$399/mo = less than $13 per day — less than an hour of a junior SEO analyst

Prices in USD. Monthly billing.

Limited access — we evaluate each request to guarantee results

Doesn't fit these tiers? Let's talk directly.

Request demo

FREQUENTLY ASKED

What people ask
before signing up.

CLICON-LOTUS se diferencia de herramientas como Semrush al centrarse exclusivamente en el rastreo de bots de modelos de lenguaje (como GPTBot y ClaudeBot) en lugar de algoritmos de búsqueda tradicionales. En lugar de analizar tráfico histórico, nuestro sistema genera archivos ejecutables llms.txt y datos estructurados JSON-LD listos para deploy, gestionando proactivamente la indexación en motores generativos.

A diferencia de Profound, que opera principalmente en inglés para el mercado global, CLICON-LOTUS está especializado técnicamente en el idioma español y la región LATAM. Además, utilizamos nuestro exclusivo Bleed Model para cuantificar el impacto financiero en USD basándonos en el valor de conversión real de su sitio y el citation gap frente a la competencia.

Implementamos un ciclo autónomo que detecta cambios en el contenido de la competencia mediante hash diff y actualiza automáticamente el código GEO. A través de nuestro MCP Server nativo, nos integramos directamente con entornos de desarrollo como Claude y Cursor vía streamable-http (en lotus.clicon.app/mcp/), entregando output ejecutable (llms.txt y JSON-LD deployable) en lugar de recomendaciones estáticas en PDF.

Ofrecemos una solución Agency White Label completa. Las agencias pueden generar reportes en PDF y acceder a un dashboard totalmente personalizado con su propia marca, sin ninguna mención a Clicon. Esto permite a las agencias presentar métricas auditables de ROI en búsqueda generativa directamente a sus clientes B2B y directores financieros (CFOs).

Mientras que Writesonic y Superlines se enfocan en la generación de contenido, CLICON-LOTUS es una plataforma técnica de Generative Engine Optimization. Nuestra ventaja radica en la creación de artefactos técnicos ejecutables y la cuantificación financiera de la pérdida de visibilidad, ofreciendo integraciones avanzadas como nuestro servidor MCP nativo para desarrolladores y reportes de marca blanca para agencias.

06 // Founder

Who's behind
Lotus.

Martín Endara — Founder & CEO, CLICON

25 years building digital products. I led digital marketing agencies serving Fortune 500 clients. I designed e-commerce platforms, SaaS products, and automation systems before "agentic" was a buzzword.

Lotus wasn't born from a pitch deck — it was born from watching LLMs rewrite the rules of digital visibility while nobody in LATAM was measuring the real impact. Every line of code, every formula in the Bleed Model, and every industry benchmark was built to solve a problem I faced firsthand as an operator: knowing exactly how much revenue you're leaving on the table and having the code to recover it.

I taught at the graduate level — Digital Marketing, E-commerce and Innovation at leading universities across Latin America for a decade. (UADE / USFQ / UISEK)

MBA (Universidad de León)·AI Product Manager (Duke University)·AI & Cybersecurity (IBM)·Music Business (Berklee College of Music)

07 // GEO Intelligence