Created: June 30, 2025
The Explorer section reveals exactly what AI models explore when processing prompts, including intermediate queries and all consulted sources. This comprehensive database helps you understand how AI systems research and formulate their responses.
Watch the Complete Walkthrough:
For a detailed demonstration of the Explorer section features, view the full video tutorial showing the interface and database functionality in action.
What is the AI Explorer Section?
The Explorer section provides complete transparency into AI model behavior by showing intermediate queries generated after prompts and all sources consulted during research. This visibility helps you understand exactly how AI systems gather and process information to create responses.
Explorer Database Overview
Comprehensive Prompt Analysis
The Explorer displays an overview of all executed prompts with customizable filtering options. Users can adjust time periods and model selections to focus their analysis. For example, viewing over 500 prompts executed across models with 1,526 total links provides substantial data for optimization insights.
Database Functionality
The Explorer functions as a proper database with advanced filtering capabilities. Key features include:
- Export to CSV for data analytics integration
- Excel-compatible data formats
- Comprehensive filtering by multiple criteria
- Real-time data updates and tracking
Intermediate Query Intelligence
Understanding AI Research Patterns
The Explorer automatically retrieves intermediate queries for Anthropic and Google Gemini models. When AI processes prompts, it generates research queries to gather relevant information from various sources and indexes.
SEO Strategy Enhancement
Intermediate queries represent a new category of search behavior that differs from traditional human keyword searches. These automated queries are:
- Generated automatically by AI models
- Increasing dramatically in volume
- Critical for future content optimization
- Different from natural human search patterns
Strategic Content Optimization
Understanding intermediate queries helps create content optimized for AI research patterns. This represents a significant addition to existing SEO strategies, targeting how AI systems actually search for and evaluate information.
Source and Domain Analysis
Multi-Dimensional Filtering
The Explorer allows analysis by various dimensions including:
- Source domains and websites
- Specific AI models used
- Time periods and date ranges
- Prompt categories and types
Granular Data Extraction
Users can extract specific data sets for targeted optimization work. Whether focusing on owned assets or third-party sources, the Explorer provides granular access to:
- Individual prompt performance
- Model-specific behavior patterns
- Source credibility and usage frequency
- Domain authority and citation patterns
Strategic Applications
Content Strategy Development
The Explorer helps identify content gaps and optimization opportunities by showing exactly which sources AI models consult. This enables strategic improvements to competitive positioning in AI search results.
Third-Party Relationship Building
By analyzing third-party sources frequently consulted by AI models, brands can identify potential partnership opportunities and influential platforms in their industry.
Future Optimization Preparation
The Explorer provides foundational data for upcoming optimization features, helping users understand current AI behavior patterns before implementing strategic improvements.
Frequently Asked Questions
What does the Explorer section show?
The Explorer section shows what AI models explore when processing prompts, including intermediate queries generated after prompts and all sources consulted during the research process. It provides complete transparency into AI model behavior.
How many prompts and links can the system track?
The Explorer can track extensive data sets, such as over 500 prompts executed across models with more than 1,526 total links. Users can adjust time periods and model selections to filter the data according to their analysis needs.
What are intermediate queries and why are they important?
Intermediate queries are automated research queries generated by AI models like Claude 4 when processing prompts. Unlike natural human keywords, these automated queries represent how AI systems actually search for information, and their volume is increasing dramatically.
How can the Explorer enhance SEO strategy?
The Explorer reveals AI-generated search patterns that differ from traditional human searches. Understanding these intermediate queries helps create content optimized for how AI models actually research topics, representing a significant addition to existing SEO strategies.
What filtering and export options are available?
The Explorer functions as a comprehensive database with advanced filtering by source, domain, model, and time period. Users can export data to CSV format for integration with data analytics tools or Excel for further analysis.
How can you use the Explorer for content optimization?
The Explorer allows granular analysis of which sources AI models consult for specific prompts and models. This helps identify optimization opportunities for both owned assets and third-party sources that influence AI responses.
What makes the Explorer valuable for understanding AI behavior?
The Explorer provides detailed insights into AI research patterns, showing exactly how models gather and process information. This transparency helps users understand current AI behavior patterns and prepare for future optimization opportunities.