Legal Content &
Entity Graph Architecture

Authoritative content designed to educate clients and feed AI recommendation engines.
The Legal Problem

Your firm’s expertise is locked inside billable hours.

Unpublished authority earns nothing.

The partners hold decades of specialist knowledge, and almost none of it exists in a form a client can read or an AI engine can cite. What does get published is usually generic commentary written by an agency with no grounding in legal practice, indistinguishable from every other firm’s.

AI recommendation engines answer client questions by citing whoever documented the answer first and structured it clearly. When your practice areas are represented by thin service pages and your partners by a resume, the engines have nothing to attribute to your firm—so they attribute it to the firm down the road.

What Is Entity Graph Architecture?

The map AI uses to decide who to cite.

AI engines don’t read pages—they map entities (your firm, partners, services, and regions) and how they connect. A good article isn’t enough; AI requires structural proof that your partner delivers that expertise in that jurisdiction.

Most firm websites leave this data fragmented. Entity graph architecture connects your partners, practice areas, and track record into a machine-readable map—ensuring ChatGPT and Perplexity cite your firm.

The Solution

Four builds that make your firm citable.

01

Knowledge Graph & Schema Engineering

Transforming unstructured partner expertise into custom JSON-LD schemas and semantic entity nodes that search crawlers and LLMs consume directly.

02

Asynchronous Partner Voice Extraction

Converting 15-minute partner audio briefs into high-authority practice group insights—zero drafting or typing required by your fee-earners.

03

LLM Citation & Retrieval Optimization (GEO)

Structuring practice area guides so ChatGPT, Perplexity, Gemini, and Claude synthesize your firm as the definitive authority in your jurisdiction.

04

Settlement & Judgment Track Record Databases

Formatting past transaction histories, litigation outcomes, and regulatory wins into structured, machine-readable databases—allowing corporate general counsel and LLMs to immediately verify your firm’s practice depth.

Site Architecture Comparison
Traditional legal site
<HTML>

Flat HTML pages

Documents with nothing declaring what they are.

Practice pagePartner pageBlog

Disconnected pages

Islands: no link from partner to practice to place.

No entity graph

Scattered facts an engine cannot attribute.

✕
Unindexed by AI
Ignored by LLMs
MTM entity architecture

Targeted, authoritative expertise

Written for the matter a client arrives with.

"@type": "LegalService"
"employee": "Partner"
"knowsAbout": "Practice"
"areaServed": "Region"

Schema mapping

Partner, practice and region declared as linked.

One connected map

Every claim traced back to your firm.

✓
Cited across AI search
Recommended by LLMs
Next Step

Ready to see where your firm stands in AI search?

Start with diagnostic data, not agency guesswork.

Before committing capital to a new website, digital advertising, or legal content; senior counsel need baseline diagnostic data. We audit your firm’s digital presence across ChatGPT, Gemini, Perplexity, and Claude to pinpoint exact visibility gaps. 10-day turnaround. Zero billable hours required from your partners.

AI Search Audit 10-day turnaround
Commission the $2,500
AI Search Audit →
Measured across
ChatGPTGeminiPerplexityClaude
Prefer to discuss your practice areas first? Schedule a structured 20-minute discovery call with founder Sean Hofer to review your target practice areas, examine your current search intake, and confirm how MTM scales for your firm size. Schedule a Discovery Call with Sean
morethanmarketing.co.nz | Specialist Legal Search & AI Growth Architecture | NZ · AU · USA