Make Your Knowledge Machine Readable
We start by mapping your entities and relationships. Products, models, materials, processes, locations, standards, suppliers, and brands sit in a clean taxonomy with controlled names and IDs. That taxonomy drives page types and content models across your site.
Next, we apply JSON-LD using schema.org types across each template. Product, Service, HowTo, FAQPage, Organization, ItemList, BreadcrumbList, VideoObject, and ImageObject are implemented with consistent keys and stable URLs. Units are normalised to AU metric, with notes for AS/NZS, NCC, RCM, and WHS where relevant.
We store canonical facts in your CMS or PIM with versioning and date stamps, then publish them to pages, feeds, and sitemaps. Internal linking patterns create clear hubs and lists that reduce crawl depth. Media gets captions, transcripts, and IPTC metadata so it can be referenced and cited by AI systems.
Entity and Taxonomy Model
Schema and Technical Markup
Citations and Provenance Signals
Product and Service Data Structured for Answers
We turn product and service data into clear, query-ready information. Product pages include GTIN, MPN, brand, model, dimensions, weights, materials, compatibility, installation notes, and safety information using Product, Offer, and HowTo schema. Variant matrices are flattened into stable URLs or parameter rules that crawlers can reach without duplicate traps.
We handle AU specifics: metric units, AS/NZS references, RCM compliance, and relevant NCC clauses. Availability, lead times, and price ranges are published through controlled fields. FAQs target high-friction queries, and we add ItemList pages for comparison sets. Media is described with VideoObject and ImageObject, including captions and transcripts so AI systems can cite them. Everything maps back to a clean taxonomy and a central facts table, so changes roll through without breaking structure.
Authoritative Pages AI Can Cite
We build canonical reference pages that answer specific questions with sources and dates. Each page carries author bylines with Person schema, Organisation details, and ContactPoint for technical or safety queries. We publish datePublished and dateModified, add change logs for key facts, and link to standards or test data where allowed.
FAQs, HowTos, and glossaries sit in a predictable structure with anchors that don’t change. Where you publish PDFs, we add proper metadata, version numbers, and deep links back to the live page. Video transcripts and image captions are indexed and referenced in JSON-LD. The outcome is content that LLMs can parse, verify, and cite, and that your team can maintain without guesswork.
Get Your Content Ready for AI Search
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