Frequently Asked Questions

LLMPageRank is an AI memory analysis platform that tracks how major language models (GPT-4, Claude, Gemini, LLaMA, etc.) remember and perceive brands. We measure consensus across 8+ AI models to identify memory drift, consensus gaps, and potential AI hallucination risks for your brand.

Our platform systematically queries major AI models about domains and brands, then analyzes their responses for consistency, accuracy, and sentiment. We cross-reference AI outputs with real-world data sources to identify discrepancies and track how brand memory evolves over time. The result is a comprehensive memory consensus score and drift analysis.

Memory Theater is our signature brand analysis experience that reveals how AI models remember your specific brand. It shows the gap between AI consensus and reality through interactive visualizations, voice analysis from multiple models, and temporal drift tracking. Think of it as a comprehensive audit of your brand's digital memory footprint.

AI memory is not traditional storage but probabilistic recall based on training data patterns. When an AI model "remembers" your brand, it's reconstructing information from billions of text patterns it learned during training. This memory can be incomplete, outdated, or biased depending on what information was most frequently associated with your brand in the training data.

Memory drift occurs when an AI model's perception of a brand diverges from current reality over time. This happens because AI models are trained on historical data and may retain outdated information, positive or negative associations from past events, or incomplete understanding of recent changes. For example, an AI might still describe a company as "innovative startup" when it's now a Fortune 500 company.

AI hallucination for brands occurs when AI models generate confident but factually incorrect information about your company. This might include wrong founding dates, incorrect business models, false partnerships, or entirely fabricated achievements. Unlike memory drift (outdated but once-accurate info), hallucination involves information that was never true.

AI consensus is what multiple AI models agree about your brand, while reality is the actual current state of your business. High consensus doesn't guarantee accuracy - multiple models can consistently share the same outdated or incorrect information. Our platform measures both consensus strength and reality alignment to identify dangerous gaps.

AI models increasingly influence customer decisions through chatbots, search results, recommendation systems, and content generation. If AI models remember your brand incorrectly, they may provide wrong information to potential customers, partners, or investors. This can impact sales, partnerships, hiring, and overall brand reputation in the AI-driven economy.

Poor AI memory can lead to: 1) Lost sales when AI recommends competitors instead of your brand, 2) Investor confusion from outdated financial information, 3) Talent acquisition issues from incorrect company descriptions, 4) Partnership problems from inaccurate capability assessments, 5) Customer service issues when AI assistants provide wrong information about your products.

Brands with accurate AI memory gain advantages through: 1) Better visibility in AI-powered search and recommendations, 2) Accurate representation when prospects ask AI assistants about solutions, 3) Correct positioning during AI-generated competitive analyses, 4) Proper context when AI creates market summaries or investment reports, 5) Enhanced brand recall in AI-assisted decision making.

We currently track 8+ major language models including: GPT-4 (OpenAI), Claude-3 (Anthropic), Gemini (Google), LLaMA-2 (Meta), PaLM (Google), Mixtral (Mistral AI), and others. We continuously add new models as they become available and gain market adoption. Each model is queried systematically with standardized prompts to ensure consistent comparison.

Memory scores are recalculated daily for active monitoring, with trend analysis updated in real-time as new data becomes available. High-priority domains may be updated multiple times per day. Historical data is preserved to track memory evolution over time. Enterprise customers can request custom update frequencies for critical monitoring.

We validate AI responses against authoritative sources including: business registries, financial databases, news archives, company official communications, regulatory filings (SEC, etc.), domain registration records, social media verification, and third-party business intelligence platforms. This multi-source approach ensures comprehensive reality checking.

Our memory score algorithm weighs: 1) Consistency across models (consensus strength), 2) Accuracy compared to verified facts (reality alignment), 3) Confidence levels expressed by each model, 4) Recency of information recalled, 5) Completeness of brand understanding. Scores range from 0-100, with higher scores indicating stronger and more accurate AI memory.

Brand managers use our platform to: 1) Monitor how AI describes their brand across different models, 2) Identify outdated or incorrect brand information in AI systems, 3) Track sentiment and positioning changes over time, 4) Benchmark against competitors' AI memory performance, 5) Prepare reports for leadership on digital brand health, 6) Proactively address AI hallucination risks before they impact business.

SEO professionals leverage our platform to: 1) Understand how AI-powered search features represent their clients, 2) Optimize content strategy for AI model training data, 3) Monitor brand entity recognition across AI systems, 4) Track the evolution of AI understanding for target keywords, 5) Prepare for the AI-driven future of search where traditional SEO metrics may be supplemented by AI memory metrics.

Marketing teams use our insights to: 1) Understand how AI models position their brand in the competitive landscape, 2) Identify messaging gaps where AI memory doesn't reflect current positioning, 3) Create content strategies that improve AI model understanding, 4) Monitor the effectiveness of PR campaigns on AI brand perception, 5) Prepare talking points for when prospects ask AI assistants about their solutions.

We offer two main plans: 1) Gracie Plan ($7/month) - 100 API calls, 10 domains, basic memory tracking, shareable reports, perfect for small businesses and individual marketers. 2) Oracle Plan ($2000/month) - 50 domains, real-time alerts, 5D tensor analysis, private API access, sentiment grounding across multiple data sources, designed for enterprises and agencies.

Oracle Plan includes: 1) Real-time monitoring with webhooks and alerts, 2) Sentiment grounding across stock prices, Reddit discussions, news sentiment, and financial data, 3) 5D tensor analysis (domain × model × time × metric × context), 4) Private API access with custom rate limits, 5) Advanced analytics and custom reporting, 6) Priority email support with dedicated account management.

Getting started is simple: 1) Visit our homepage and explore the Memory Shrine demo, 2) Check our leaderboard to see how other brands perform, 3) Search for your domain to see current AI memory status, 4) Sign up for the Gracie Plan to start tracking, 5) Use our brand analysis tools to identify improvement opportunities, 6) Contact sales for enterprise needs or custom solutions.

Yes! Our Memory Shrine offers a comprehensive demo experience where you can explore AI memory analysis for sample brands. You can also search any domain to see basic memory insights. The Gracie Plan starts at just $7/month with no long-term commitment, making it easy to test our platform with your actual brand data.

Yes, we provide comprehensive API access for both plans. The Gracie Plan includes 100 API calls monthly for basic integrations. The Oracle Plan offers private API access with higher rate limits, webhooks for real-time notifications, and custom endpoints for enterprise workflows. Our API allows you to integrate AI memory monitoring into your existing marketing and business intelligence tools.

LLMPageRank integrates with: 1) Marketing automation platforms via API, 2) Business intelligence tools through data exports, 3) Slack and email for real-time alerts, 4) CRM systems for brand health scoring, 5) Content management systems for optimization recommendations, 6) Analytics platforms for comprehensive brand monitoring dashboards.