Definition
Machine discoverability is the technical layer underneath AI visibility: whether crawlers, AI models, and agents can actually access a site, parse its content, and extract accurate, structured facts from it. A brand can have a strong story and still be machine-invisible if the underlying site is hard to crawl, missing structured data, or inconsistent about basic facts.
Trocial’s technical and entity readiness check evaluates six real signals for every scan: crawlability (can the site be reached and parsed at all), metadata completeness, canonical tag presence, schema markup presence, page specificity (does a page answer one clear question or many vague ones), and proof consistency (do the facts on the page match what is stated elsewhere).
These are binary, checkable items - not opinions - which is why they are one of the more reliable levers a team can move quickly, compared to slower-moving signals like third-party authority.
Search crawlers, AI answer engines, and autonomous agents all depend on the same underlying access: can the content be fetched, and can facts be extracted cleanly. Fixing machine discoverability issues therefore tends to help every downstream surface at once, rather than optimizing for one channel in isolation.
Trocial organizes the facts extracted and confirmed during a scan into BrandGraph: company facts, products, capabilities, markets, proof, citations, and competitive context, plus any brand information a team has explicitly approved. BrandGraph is the structured record Trocial builds from a scan, not a claim that it is already published or indexed everywhere.
Fetch a page with a plain text tool rather than a browser: if the category, offer, and pricing are not readable in the raw response, a crawler or model may be missing them too. Pair that with checking for a canonical tag and basic schema markup - the two most common gaps Trocial’s readiness check finds.
Schema markup is structured data embedded in a page (for example, describing an organization or a product) that machines can parse directly, instead of inferring meaning from prose. Trocial’s readiness check flags whether it is present.
Trocial generates draft fixes - such as schema blocks and an llms.txt draft - for review. Nothing is auto-published to a customer’s website; a person reviews and approves changes before they go live.