How Do You Use VectorGap for
AI Brand Intelligence?
Everything you need to monitor AI perception, optimize for GEO, and manage your brand's presence across AI systems.
What Can You Learn from VectorGap Documentation?
VectorGap documentation is organized to help you accomplish specific goals—whether you're just getting started with AI brand perception monitoring, looking to implement advanced GEO optimization, or building custom integrations with our API. Each section focuses on practical outcomes rather than abstract concepts.
Start with our Quick Start Guide to run your first perception audit within minutes. From there, explore deeper topics: learn how LLM perception monitoring works across ChatGPT, Claude, Gemini, Perplexity, and Grok; understand how to build a Knowledge Base that grounds AI responses in verified facts; discover GEO optimization techniques that improve your visibility in AI-generated answers.
For deeper learning, check out VectorGap Academy—our certification program covering GEO mastery, LLM perception psychology, citation authority building, competitive intelligence, and brand perception management. The Academy combines conceptual knowledge with hands-on exercises using VectorGap's tools.
Which Documentation Topic Do You Need?
Browse by category to find guides, tutorials, and reference documentation for every VectorGap feature.
Our documentation is organized around the core workflows that VectorGap enables. Getting Started guides walk you through account setup, brand creation, and running your first perception audit—most users complete this in under 10 minutes. From there, you can dive into specific capabilities based on your immediate needs, whether that's understanding your Brand Perception Index, setting up competitive tracking, or configuring integrations.
LLM Perception Monitoring documentation explains how VectorGap tracks what AI systems say about your brand. You'll learn about the different audit types (comprehensive vs. targeted), how to interpret results across ChatGPT, Claude, Gemini, Perplexity, and Grok, and how to set up automated scheduling so you're always monitoring. The Knowledge Base section covers document uploads, hallucination detection, and how to build a verified truth source that grounds AI responses in accurate information.
For technical teams, the API & Integrations section provides everything needed to build custom workflows. Our REST API documentation includes authentication guides, endpoint references, webhook configuration, and rate limit information. Each guide includes code examples in multiple languages and practical use cases. Security & Compliance documentation addresses enterprise requirements including GDPR data handling, SOC 2 preparation, and data processing agreements.
Frequently Asked Questions About VectorGap
Common questions about getting started, core concepts, and how VectorGap works.
Getting started with VectorGap takes about 5 minutes. First, create a free account at vectorgap.ai/register. Then create your first brand by entering your company name and website URL. VectorGap will automatically run an initial perception audit across ChatGPT, Claude, Gemini, Perplexity, and Grok. Within minutes, you'll see your Brand Perception Index (BPI) score and detailed metrics for how AI systems perceive your brand.
The Brand Perception Index (BPI) is VectorGap's composite score measuring how accurately and favorably AI systems perceive your brand. It combines six metrics: Accuracy (factual correctness), Sentiment (positive vs negative tone), Coverage (mention frequency), Credibility (authority signals), Visibility (prominence in responses), and Recommendation (likelihood AI suggests your brand). Each metric is scored 0-100, and the BPI is a weighted average calibrated against industry benchmarks.
The Knowledge Base creates a verified truth source about your brand. Upload your documentation, product specs, press releases, and other authoritative content. VectorGap indexes this content in a temporal knowledge graph powered by Neo4j and Graphiti. When auditing LLM responses, we compare what AI systems say against your Knowledge Base to detect hallucinations—incorrect claims, outdated information, or misattributed facts. You receive accuracy scores and specific contradiction alerts.
VectorGap monitors AI perception across five major LLM providers: ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), Perplexity, and Grok (xAI). Each provider is audited independently using standardized prompts to ensure consistent measurement. You can view aggregate BPI scores across all providers or drill down into individual provider metrics to understand where your brand perception varies by AI system.
Can't Find What You're Looking For?
Our support team is here to help with any questions about VectorGap features, implementation, or best practices.