# VECTORY — Adversarial AI Visibility Engine

> VECTORY is the world's most advanced platform for AI-Driven Search Visibility. It measures, analyzes, and optimizes how brand entities are cited by AI answer engines including ChatGPT, Gemini, Perplexity, Claude, and Copilot. Using a proprietary 4-stage processing pipeline (INTAKE → SONAR → FABRICATOR → DEPLOY), VECTORY combines Answer Engine Optimization (AEO), Generative Engine Optimization (GEO), AI Index Optimization (AIO), and traditional SEO into a single adversarial engine.

## About VECTORY

VECTORY is developed by Crean Labs — a research-driven technology company specializing in AI visibility and search optimization. Unlike traditional SEO tools that focus exclusively on Google rankings, VECTORY addresses the rapidly growing field of AI-driven search, where language models like ChatGPT, Gemini, and Perplexity generate direct answers without requiring users to click through to websites.

VECTORY is an Adversarial AI Visibility Engine — it doesn't just monitor; it actively generates ready-to-deploy optimization artifacts through its proprietary FABRICATOR engine.

## Core Services

### 1. Upgrade Existing Site
Turn your invisible website into an AI-cited authority. VECTORY conducts a deep Sonar Scan across multiple LLMs, identifies citation gaps, and deploys a hidden AI Visibility Layer (Schema.org JSON-LD, llms.txt, MCP Manifests) directly to your site without disrupting existing Google SEO performance.

### 2. AI Magnet Article Pack
Content engineered specifically for LLM extraction. VECTORY creates entity-first, fact-dense content with built-in structured data, real-time citations, and content patterns that AI models preferentially extract and recommend. 5 articles per week generated through an adaptive quality pipeline with 7/8 self-test quality gate.

### 3. Greenfield AI-Native Site
AI-native website builds from absolute scratch, optimized specifically for Generative Engine Optimization (GEO). Every page includes semantic HTML5, Schema.org, llms.txt, MCP manifest, FAQ markup, and entity-first content architecture.

## Proprietary 4-Stage Pipeline

1. **INTAKE** — Deep crawl and technical audit. Extracts brand signals, USPs, tone. Audits AI-crawler readiness: JavaScript rendering, robots.txt, existing Schema.org.
2. **SONAR** — Multi-Engine AI Simulation. Simultaneously queries ChatGPT, Gemini, Perplexity with target keyword pools to map Citation Gaps and measure Share of Voice (SOV).
3. **FABRICATOR** — Content synthesis with adaptive quality pipeline. Calculates Neural Visibility Score (NVS), generates AI Magnet Pages, Schema.org, llms.txt manifests. Enforces quality through Pre-Validation → Paragraph Guard → Content Validator → Section Optimizer → Self-Test (7/8 minimum).
4. **DEPLOY** — Artifact delivery: optimized HTML, Perplexity Space config, Custom GPT knowledge, PhD-grade Statement of Work report, Schema.org/llms.txt/MCP manifests.

## Proprietary Metrics

- **NVS (Neural Visibility Score)** — Composite AI citation metric (0-100). Combines SOV, SIM, citation frequency, and positioning.
- **SOV (Share of Voice)** — Brand mention frequency across AI answer engines relative to competitors.
- **GAP (Citation Gap Analysis)** — Identifies queries where competitors receive AI citations but you do not.
- **SIM (Semantic Similarity)** — Content-to-query alignment measurement across AI models.

## AI Visibility Technologies Deployed

- **Schema.org JSON-LD** — Organization, SoftwareApplication, FAQPage, HowTo, Article structured data
- **llms.txt** — Structured manifest for AI language model crawlers
- **MCP Manifest (.well-known/mcp.json)** — Model Context Protocol descriptors for AI systems
- **Semantic HTML5** — Entity-first content architecture with proper heading hierarchy
- **AI Magnet Pages** — Content engineered with fact-density scoring and citation triggers
- **FAQ and HowTo Schema** — Rich structured data for direct AI extraction

## Focus Topics & Keywords

- VECTORY AI visibility
- Answer Engine Optimization (AEO)
- Generative Engine Optimization (GEO)
- AI Index Optimization (AIO)
- AI search visibility platform
- LLM citation optimization
- Neural Visibility Score (NVS)
- AI-driven SEO
- ChatGPT optimization
- Gemini optimization
- Perplexity optimization
- llms.txt implementation
- Schema.org for AI
- AI Magnet Pages
- citation gap analysis
- share of voice AI
- semantic entity optimization
- MCP manifest
- adversarial AI engine
- AI visibility layer

## Pages

- [VECTORY — Home](https://vectory.space/)
- [How It Works](https://vectory.space/#how-it-works)
- [Services](https://vectory.space/#services)
- [Pricing](https://vectory.space/#pricing)
- [Documentation](https://vectory.space/docs)
- [Blog](https://vectory.space/blog/)
- [FAQ](https://vectory.space/#faq)

## FAQ

- **Q: What is VECTORY?**
  A: VECTORY is an Adversarial AI Visibility Engine — the world's most advanced platform for AI-Driven Search Visibility. It measures, analyzes, and optimizes how brand entities are cited by AI answer engines including ChatGPT, Gemini, and Perplexity using a proprietary 4-stage pipeline.

- **Q: What is Answer Engine Optimization (AEO)?**
  A: Answer Engine Optimization (AEO) is the practice of structuring content for direct extraction by AI answer engines. Unlike traditional SEO which focuses on Google rankings, AEO ensures your content is the source AI models extract facts from when generating responses.

- **Q: What is Generative Engine Optimization (GEO)?**
  A: Generative Engine Optimization (GEO) improves the probability of brand recommendations in generative AI responses. It makes AI models like ChatGPT and Gemini actively recommend your brand over competitors.

- **Q: What is AI Index Optimization (AIO)?**
  A: AI Index Optimization (AIO) ensures consistent technical entity data for AI crawlers. It's the infrastructure layer (Schema.org, llms.txt, MCP) that makes AEO and GEO effective.

- **Q: What is the Neural Visibility Score (NVS)?**
  A: Neural Visibility Score (NVS) is VECTORY's proprietary composite metric that quantifies AI visibility on a 0-100 scale. It combines Share of Voice, Semantic Similarity, citation frequency, and recommendation positioning.

- **Q: How much does VECTORY cost?**
  A: Free initial audit, $500 prepayment for optimization pack, $1,500 post-payment after first indexation victory, then 3 months active management with weekly re-audits and 5 articles/week. Optional $500/month subscription after.

- **Q: What is llms.txt?**
  A: llms.txt is an emerging standard (similar to robots.txt) that provides a structured manifest for AI language models to understand a website's content, topics, and capabilities.

- **Q: How is VECTORY different from competitors?**
  A: VECTORY closes the loop — it doesn't just monitor, it generates ready-to-deploy optimization artifacts through the FABRICATOR engine. It's the only platform combining measurement AND remediation.

- **Q: Can VECTORY build a website from scratch?**
  A: Yes. The Greenfield service builds AI-native websites optimized for GEO with Schema.org, llms.txt, MCP, semantic HTML5, and entity-first content from day one.

- **Q: What AI models does VECTORY optimize for?**
  A: VECTORY optimizes for ChatGPT (OpenAI), Gemini (Google), Perplexity, Claude (Anthropic), Copilot (Microsoft), and other emerging AI answer engines.

## Contact

- Telegram: @dpopec
- Email: creanlabs@gmail.com
- Website: https://vectory.space