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, Grok, and Mistral; 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.
The docs hub is meant to help existing evaluators and teams get to a usable next step fast. It should function like a support center, not like a second acquisition homepage.
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, Grok, and Mistral, 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.
Start with the Quick Start guide, open your workspace, add your first brand, and run the first audit. The docs hub is for existing evaluators and teams who need the shortest path to a usable next step, not a second acquisition flow.
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 supports the main LLM providers currently exposed in the product, such as ChatGPT, Claude, Gemini, Perplexity, Grok, and Mistral where enabled. Provider availability depends on plan and workspace configuration, and each included provider is audited independently.
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.
If you are blocked after Quick Start, use the contact page from the docs navigation for support.