Structured data infrastructure for AI retrieval
Nodal Layer is the structured data infrastructure that makes your brand legible to AI systems — llms.txt at the domain root, JSON-LD on every page, and explicit crawler permissions that signal your brand welcomes accurate retrieval. Machine-readable, but authored by you — your brand decides what the machine reads, rather than letting it infer from whatever it can scrape.
Nodal Layer closes the visibility gap — the space between the brand you've built and the brand AI systems can actually find and read.
A brand without structured data is a brand that relies on AI systems to guess from unstructured content. Nodal Layer makes the guessing unnecessary — your brand identity, product catalogue, and conversational guidance, declared explicitly and served in formats AI systems are built to read.
Three layers. One legible brand.
Each layer addresses a different surface where AI systems encounter your brand. Together they make your brand readable at domain, page, and crawler level.
Service 1
Site level — llms.txt
A plain-text declaration at your root domain. Brand identity, product catalogue, use cases, and conversational guidance — written for LLM retrieval, not for humans.
Learn about llms.txt →Service 2
Page level — JSON-LD
Structured data embedded in every page head. Per-product and per-service declarations using schema.org extended with the Brand Rosetta vocabulary.
Learn about JSON-LD →Service 3
Access level — robots.txt
Explicit permissions for known AI crawlers. A signal that the brand welcomes accurate retrieval rather than blocking or ignoring it.
Learn about access rules →How it works
Declared once.
Maintained continuously.
A four-phase process from audit to deployment. The first two phases are discovery and design. Phase three ships the layer and validates it against live AI surfaces. Phase four keeps it current as the brand evolves.
Get startedAudit current state
Map every emission point, score existing structured data against AI-readiness criteria.
Design the layer
Author llms.txt, extend JSON-LD schema per page type, configure crawler rules.
Deploy and validate
Ship the layer, run grounding tests against major LLM surfaces.
Monitor and maintain
Quarterly reviews as brand and products evolve, schema updated with every major launch.
What the layer looks like
An llms.txt declaration and a JSON-LD schema — both authored for AI retrieval, both grounded in your canonical record.
The gap is already open.
From the 2026 Brand Readiness in the Canadian Market study — 51 brands, across six categories.
Median AI readiness score across 51 Canadian brands
Brand in 51 with an llms.txt file deployed
Of product catalogues invisible to AI crawlers
Brand Readiness in the Canadian Market, 2026 — Nodal Strategy
Implicit personality held brands together for thirty years. The next thirty will be built on explicit identity, machine-readable and governed continuously.
Nodal Layer is the foundation. Oliver Norton and Nodal Strategy build it with you.
Talk to us about your nodal layer →