Multi-LLM visibility platform that monitors how ChatGPT, Claude, Gemini, and Perplexity mention and cite brands in AI-generated answers. Real-time analytics and competitive intelligence.
What I Learned
Multi-provider orchestration is harder than it looks — each LLM has different response patterns
The scoring methodology matters more than the platform
This market is moving fast — first-mover advantage is real but fragile
The Problem
Brands have no visibility into how AI assistants represent them. When someone asks ChatGPT "What's the best CRM?", brands don't know if they're being mentioned, how accurately, or compared to whom.
The Approach
Built a monitoring platform that queries each major AI provider and analyzes responses for brand mentions, sentiment, accuracy, and competitive positioning. Generates an "AEO Readiness Score" that quantifies AI visibility.
Architecture Decisions
Multi-LLM orchestration layer
AEO Readiness Score framework (0-100 with 4 weighted dimensions)
Real-time citation tracking and analytics
Cost tracking and attribution per query
Why I Built It This Way
Built multi-LLM from start rather than single-provider
Created proprietary AEO Readiness Score methodology
Implemented cost tracking at query level for margin visibility
Technology Stack
Next.js 15React 19TypeScriptSupabasePostgreSQLOpenAI APIAnthropic APIGoogle AI APIPerplexity APITailwind CSS
Outcomes
First-mover platform for AI answer visibility
Proprietary AEO Readiness Score
Multi-tenant architecture
Competitive intelligence automation
Started: 2024-11
Ongoing (Phase 22+)