AVO Series · Phase 02 of 03

Build —
Create Content AI Will Cite.

AVO content must be extractable, verifiable, and modular — and always compliance-ready. Building means more than writing: it requires metadata, provenance, and an MLR-capable production line.

≤50Words per Citable Answer Block
4MLR Metadata Fields per Page
1Source Tag per Claim, No Exceptions

The Pyramid Chunking Principle

Start with a one-sentence direct answer, then a supporting 2–3 sentence explanation, then bullet evidence. Use question H2s and compact answer blocks under 50 words that can be cited as-is.

01
Layer 01
Direct Answer
One sentence. No hedging, no preamble — the answer a model can lift and cite directly.
02
Layer 02
Context Paragraph
2–3 sentences of supporting explanation that frame the answer without diluting it.
03
Layer 03
Evidence List
A 3-item bullet list with DOI/PMID, guideline name, and approval date — fact-dense, model-preferred.
Answer (≤40 words)
“Use a one-line direct answer, a 2–3 sentence context paragraph, and a 3-item evidence list with DOI/PMID and approval date.”

Every Claim Carries Its Source

Attach a source tag to every claim: study citation (PMID/DOI), guideline name, internal clinical memo, date, and author. Publish a machine-readable bibliography or schema.org citation block per page.

◆
Requirement 01
Source Tag per Claim
PMID/DOI, guideline name, date, author — attached, not implied.
◇
Requirement 02
Machine-Readable Bibliography
schema.org citation block per page, not a static PDF reference list.
●
Requirement 03
MLR Metadata in the Header
Author, reviewer, version, and approval date for every regulated asset.

From Pages to Entity Authority

Build a lightweight medical knowledge graph — entities and relations — for your brand topics, and expose canonical IDs in page markup via JSON-LD and schema.org.

01
Artifact 01
Topic Hubs
Concise overview pages that link to evidence nodes — papers, datasheets — increasing entity authority and RAG retrieval quality.
02
Artifact 02
Prompt Book
Canonical prompts paired with ideal high-quality answers, seeded into platforms you control.
03
Artifact 03
JSON-LD Markup
schema.org Article metadata plus a custom provenance block — author, reviewDate, approvalId.

Automate the Draft. Keep the Human Sign-Off.

Standardize modular content blocks with versioning and approval metadata. Automate draft generation with LLM assistance, but preserve human-in-the-loop sign-off and a full audit trail of who changed what, when, and why.

How Do You Know It's Working?

Explore Phase 03 — the Visibility Score, RAG and retrieval testing, and the KPIs that turn AVO into a measurable, repeatable program.

Measure Visibility → Back to Discover