From Prototype to Platform
The Journey to AI Answer Visibility
We've spent 4 months building what no one else dared to quantify — how AI sees, ranks, and trusts brands.
This is the evolution of the world's first AI Search Visibility Platform.
Foundation Phase
July 2025 — Where the framework was born
Core Infrastructure Built
Established Supabase + Vercel foundation with secure pipelines and daily snapshot automation. Built the data architecture that powers our entire AI visibility platform.
Entity Schema & Context Mapping
Established canonical entity system with alias management, hierarchical taxonomy, and relationship mapping. The foundation that makes AI search visibility measurable.
TrendsCoded Platform Launch
Initial platform development with core entity tracking functionality and AI search visibility foundations. The first step toward quantifying how AI sees brands.
Core Features Phase
August 2025 — Where AI met structure
Factor Scoring System Launched
Implemented multi-criteria ranking with motivator-weighted evaluation model. This is how we measure what makes brands rank in AI responses.
Tracking & Analytics Pipeline
Built frequency & trend tracking, ranking change analysis, and list performance metrics. The intelligence layer that powers our insights.
AI Prompt Builder v1
Launched market + simulation buyer persona + motivator prompt composition engine. The tool that helps brands understand how to optimize for AI search.
Content Editor & Structured Data Builder
Released modular content architecture with visual JSON-LD builder and assistant-block framework. Making structured data accessible to every marketer.
Advanced Analytics Phase
September 2025 — Where intelligence became visible
Buyer Persona Simulation Pages (6 Markets)
Built entity ranking drift analysis pages, tracked-entity dashboards, and real-time visibility feeds. The first glimpse into how AI sees different market segments.
Sentiment Analysis Engine Integrated
Implemented motivator-aligned sentiment tracking with contextual polarity scoring. Understanding not just what AI says, but how it feels about brands.
GA4 Integration Dashboards
Launched interactive analytics with GA4 integration and AI model attribution tracking. Connecting traditional web analytics with AI search visibility.
Brand Sentiment & Share of Voice Tracking
Implemented multi-assistant visibility and trust measurement across AI platforms. The first comprehensive view of brand presence in AI responses.
AI Mention Tracking Across Models
Launched cross-assistant indexing across ChatGPT, Perplexity, Gemini, and Claude for comprehensive AI search monitoring. The complete picture of AI visibility.
AI Search Platform Phase
October 2025 — The platform era begins
AI Search Lab & Definition System
Built visibility playbooks, AI search definitions, and motivator & framework library for comprehensive AI search optimization. The knowledge base that powers everything.
Comparison & Timeline Visualizations
Implemented quadrant analysis and interactive progress timeline UX for enhanced data visualization. Making complex AI visibility data accessible and actionable.
Content Editor & Structured Data Builder
Released modular content architecture with visual JSON-LD builder and assistant-block framework. The tools that make AI optimization accessible to every team.
Database Blocks System Released
Integrated timeline & comparison blocks into Supabase CMS for dynamic content management. The infrastructure that makes our platform truly modular.
Knowledge Graph Schema & Entity Mapping
Built JSON-LD optimization and semantic relationship graph for enhanced AI search visibility. The semantic layer that makes brands discoverable by AI.
We're not done.
Each month, TrendsCoded expands what AI visibility means — across new assistants, new markets, and new motivator dimensions.
Next up: Real-time model drift detection and cross-model content verification.