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Case Study
AEO Platform Dogfooding
We built the AEO Platform to solve our own problem: understanding how AI platforms talk about us. Here is what we learned monitoring ym8.co.uk as our first domain.
4
AI Platforms
ChatGPT, Perplexity, Gemini, Claude
250+
Queries Tracked
across FinTech and AI consulting
Daily
Collection
automated visibility snapshots
17
Migrations
production-grade schema
What We Built
- Multi-provider collection engine (OpenAI, Anthropic, Google, Perplexity)
- Share of Model metrics: visibility score, citation rate, position tracking
- Auto-generated query bank from domain and topic analysis
- Content recommendations engine for improving AI visibility
Key Findings
- Perplexity cites sources most frequently — structured content gets discovered
- ChatGPT favours authoritative entities with clear topic clusters
- JSON-LD structured data correlates with better AI platform coverage
- llms.txt and quotable answer blocks measurably improve mention rates
Platform Architecture
Stack
- Next.js 16 (App Router)
- Supabase (PostgreSQL + RLS)
- Recharts dashboards
- Zustand state management
Data Pipeline
- Collector orchestrator pattern
- Parallel multi-provider queries
- Mention extraction and scoring
- Historical trend analysis
Schema
- 17 migrations
- Brands, queries, responses, mentions
- Reports, keywords, workflows
- Bot analytics, citation tags, assets
Monitoring
- 4 AI platforms collected
- 250+ queries per brand
- Daily automated collection
- Weekly report snapshots
Monitor your own AI visibility
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