The TH Analytica Framework is a methodology for assessing the technical and semantic conditions that help people, search systems and AI-assisted retrieval interpret a website consistently.
It reviews:
- a mandatory, non-scored Positioning Foundation (Layer 0) covering intended positioning, target audiences, Desired Query Space, Excluded Query Space and supporting evidence
- technical accessibility, crawlability and multilingual LLM discovery consistency
- semantic and entity clarity
- structured data and content architecture
- trust, authorship and external corroboration
- Source Integrity & Evidence Readiness, including claim-level source verification for business-critical AI answers
- AI Zero-Click Presence & Direct Action Measurement, separating observed AI-answer presence, zero-click capability, structural action readiness and attributable business outcomes
- agent readiness, Agent Governance, controlled AI outputs, Agent Communication Readiness, action boundaries, human approval and auditability
- physical-place identity and AI-glasses governance where a venue is relevant
- Personal Privacy Signal (PPS) for anonymous person-level privacy preferences and Collective Privacy Shield
The framework does not guarantee crawling, indexing, model training, citations, mentions, recommendations, leads or revenue. Different AI products use different combinations of training data, search indexes, retrieval systems and live fetches.
Every Quick Check and Full Analysis starts by separating intended positioning from what public signals currently communicate.
Quick Checks can only report observable positioning clarity. Full Analyses must establish a Positioning Brief, Desired Query Space, Excluded Query Space and evidence basis before strategic technical recommendations are prioritised.
- Technical Foundation
- Search and Open-Web Presence
- Semantic Clarity
- Trust Signals
- Strategic Communication
- Context and AI Readability
- Agent Readiness, Governance and Portability
- Source Concentration and AI Visibility Resilience
- Physical AI Readiness and Visual Governance
- Framework methodology
- Positioning Foundation / Layer 0
- Definitions
- Evidence-First Content and Citation Readiness Standard
- Source Integrity & Evidence Readiness
- AI Zero-Click Presence & Direct Action Measurement
- Local AI Data Sources & Entity Consistency
- LLM Discovery / Locale Resolution
- AI Output & Liability Readiness
- Agent Communication Readiness
- Agent Governance
- Physical AI Governance v0.1
- Personal Privacy Signal (PPS) Draft v1.0
- Mandatory Privacy-by-Design Standard
- Full-analysis applicability gate
- AI Visibility Methodology
- AI Readiness Analysis
- Machine-readable summary
For services, implementation guidance and current contact details, visit TH Analytica.
Maintainer: Thomas Hullin
Contact: thomas@th-analytica.com
Dimension 7 includes a mandatory Agent Portability module that checks whether organisation-controlled knowledge, rules, skills, interfaces and governance can be reused or migrated across compatible agent runtimes without avoidable dependency on one provider. See agent-portability.md.