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Served Artifact Ledger
Feed URL, artifact type, response hash, validation status and last build are kept separate.
Proof: which AI-readable artifact was technically delivered.
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Beconova creates and hosts machine-readable files for products, services and company data. You add a small snippet, manage data in the dashboard and Beconova updates hosted files when sources change.
Product logic
Tracker -> AI-readable Data Layer -> Proof Loop. Beconova is not just a snippet installer. Not an AI SEO OS clone: the snippet is the technical connection point between AI Visibility Tracking, AI-readable Data Layer and Proof Loop.
Answer samples, mentions, citations, competitors and sources are measured as observed samples.
Snippet, WAI, llms.txt, JSON-LD, product feeds and service feeds make maintained data machine-readable and reachable.
Feed registry, snippet status, crawler hints, actions and rechecks document what technically happened.
What the snippet actually does
The snippet points AI and search crawlers to Beconova endpoints and helps the system verify whether the technical connection is active. It makes technical observation easier, but does not replace server-side feed and log evidence. The actual files are controlled by Beconova: WAI, llms.txt, JSON-LD, product feeds, service feeds and feed HTML.
You add a small script or integration block. This is the technical starting point.
Beconova generates and hosts AI-readable files so they can be maintained and validated centrally.
You manage sources, products, services, priorities, overrides and validations in the dashboard.
Data Layer Proof Chain
Beconova separates technical delivery evidence from answer monitoring: served feeds, connected snippet, observable crawler access and schema validation.
Feed Registry, feed URL and response hash show which AI-readable artifact was served.
Snippet status shows whether the website is connected to hosted Beconova endpoints.
Crawler and bot access can be documented with verification state as technical evidence where observable.
JSON-LD and Schema.org validation show whether product, service and entity data is machine-readable and consistent.
Feed, snippet, crawler and schema evidence can be carried into the proof report and report handoff, so setup, recheck and delivery stay connected.
Delivery Evidence Anatomy
Scrunch/Profound sell the AI-agent and crawler story well. Beconova also shows which artifact was served, which access was observable and how that becomes report evidence.
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Feed URL, artifact type, response hash, validation status and last build are kept separate.
Proof: which AI-readable artifact was technically delivered.
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Bot name, IP state, user agent and verification state show whether access was observable and how strong it is.
Proof: crawler evidence without turning it into a citation or ranking guarantee.
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Feed, snippet, crawler and schema evidence are carried into recheck and report context.
Proof: technical delivery, limit and next step stay connected.
Delivered files
Active endpoints depend on product type, plan, integration and maintained data. This page does not promise inclusion in third-party AI answers.
Manifest for AI discovery and machine-readable company data.
Own data envelope for products, services, locations, booking paths, FAQs, events and team.
Compact reference for LLM crawlers and AI agents.
Schema.org data for products, services, organization, FAQ and other entities.
Product data such as name, price, availability, variants and sources.
Services, regions, opening hours, proof points and local entities.
Readable feed pages for validation, debugging and crawler access.
Automatic updates
Products, services, copy, prices, availability or manual overrides are updated in the dashboard or through integrations.
Beconova creates new AI-readable artifacts from current data and checks validations again.
The files hosted by Beconova are updated without you editing every file manually.
The dashboard shows technical signals such as snippet status, validation, feed access and crawler hints where observable.
Crawler and access signals
When AI or search systems fetch the snippet or linked feed endpoints, observable technical signals can be created. This makes technical AI-access detection much easier than relying on answer monitoring alone. It does not replace mention checks, but it shows whether AI-readable data was technically reachable.
View crawler evidenceBeconova can document which feed routes were requested where access is technically visible server-side.
User agent, IP state and verification status help separate official, suspected and unverifiable access.
Alongside mentions and citations, you get a second proof path: were AI-readable data endpoints actually delivered?
Dashboard controls
Connect websites, shops, services, manual sources and integrations.
Prioritize key claims, locations, categories, product data or service details.
Check missing required data, broken links, schema issues and feed status.
Measure again after changes to see whether data, feeds or visibility signals improved.
Visibility Monitoring uses 2, 4 or 9 core providers depending on plan; Google Search AI remains an optional beta signal.
Manage clients separately, prepare reports and use white-label delivery when booked.
Third-party AI systems decide if and when they crawl, cite or use content.
Provable
Limits
Who this is for
Product data, prices and availability stay centrally maintained for AI-readable feeds.
Online shopsServices, locations, opening hours and proof points are delivered as structured service data.
Service providersClients can be managed separately, validated and supported with reports.
AgenciesNo. The snippet connects your website with Beconova. Beconova hosts and updates AI-readable files where supported by your plan, integration and maintained data.
Yes, when relevant data sources change, Beconova can rebuild hosted artifacts and re-run validations. The exact scope depends on data source, integration and plan.
Yes. You can manage sources, products, services, priorities, manual corrections and rechecks in the dashboard. Not every setting is identical in every plan.
No. The snippet makes data technically more discoverable and auditable. Whether third-party AI systems crawl, use or cite the content is decided by each provider.
Not as a core provider. Gemini is its own provider in the provider set. Google Search AI signals can only be treated as separate optional beta signals when that measurement is configured.
The technical connection can typically be set up in 5 to 10 minutes: add website or source and install the snippet. Clean product or service data still matters.
We show which data is missing, which feeds make sense and what technical delivery would look like for your setup.