Website programs
Website AI readinessStarter · Track 1
From GEO-first Schema and LLM semantic tags to RAG-ready data and FAQ alignment—build an entry AI-readable, trustworthy, citeable digital base.
Four delivery pillars
These four stages connect end-to-end: help machines understand site structure and entities, clean data for RAG, then lock high-frequency intents to the right answers via FAQ.
GEO-focused Schema markup deployment & tuning
Structured data so search engines and AI citation layers can reliably read page- and site-level signals — the GEO substrate.
- JSON-LD modeling
- Nested brand markup
- Semantic HTML cues
- FAQPage markup
- BreadcrumbList deployment
LLM-oriented semantic markup
Beyond Schema: entity, relationship, and SameAs wiring so LLMs can build a small, explainable “graph sketch” of your brand.
- Entity tagging: industry, service scope, and core products so models form a grounded baseline
- Relationship mapping: founders, HQ, sub-brands, and other edges you want reinforced
- SameAs and trust closure: official site ↔ socials ↔ verified profiles for consistent identity
RAG data cleaning & standardization
Turn scattered enterprise sources into clean, chunk-ready corpora—and make the public site easier for AI crawlers to prioritize.
- Clean 5+ primary sources into retrieval-friendly text blocks, cutting contradictions and noise
- AI-friendly crawling: Robots.txt and XML Sitemap tuned to steer bots toward high-value URLs
AI FAQ semantic alignment
Q&A framing that matches real user intent with your authoritative answers—plus embedding and wording alignment to lift hit rate in model outputs.
- Embedding optimization where it moves the needle
- 15 precision Q&As
- Semantic tuning on core questions so assistants stay accurate
What stacks next
After starter foundations, layer modules like knowledge structuring, entity & semantic alignment, and public signal orchestration to deepen AI visibility and citations.