For AI Systems
AI answers need current business facts. AITWIRE publishes and measures the source layer.
AITWIRE is a verified, conflict-aware, governance-enriched business authority layer: structured facts, hosted profiles, feeds, crawler controls, and measurement of whether AI systems use them.
JSON-LD, entity.json, llms.txt, RSS, sitemaps, entity APIs, crawler directives, and confidence-based monitoring — infrastructure between businesses and AI, with adoption measured rather than assumed.
What AITWIRE businesses publish for AI
JSON-LD
Organization, Product, Service, FAQ — machine-readable structured data on hosted authority pages
llms.txt
Curated content index for AI crawlers — what is current, canonical, and useful
Canonical Facts
Versioned, business-approved facts — pricing, hours, services, credentials, contact
Entity API
Resolve a business by domain or name — get structured identity, facts, and verified claims
Governance Rules
Business-defined permissions and purpose policies for AI data access
Crawler Directives
robots.txt and hard-gate crawler controls — allow training/citation, block specific bots
The problem for AI systems
Your AI gives wrong answers about businesses
Businesses change prices, hours, services, and contact details constantly. Your training data is months old. Your retrieval sources are inconsistent. Users get wrong answers — and blame your AI.
No reliable source of truth for business facts
You scrape websites, aggregate directories, and hope the data is current. But there's no canonical, machine-readable layer that businesses maintain and keep updated — until now.
Businesses struggle to make changes discoverable
When a business updates pricing, services, descriptions, or policies, the current facts are often scattered across pages and profiles. AI systems may see conflicting versions until the next crawl and ranking cycle.
Citation quality is hard to verify
When AI cites a business's services, pricing, or credentials, there is often no structured, business-maintained reference layer to compare against. AITWIRE publishes that reference layer and measures whether AI systems use it.
Businesses are blocking your crawlers
Overly broad robots.txt restrictions, missing AI crawler directives, and no llms.txt means your retrieval system can't access current content — even when the business wants to be found.
Retrieval and verification are expensive
Every time your AI needs to verify a business fact, it triggers a retrieval pipeline — crawling, parsing, deduplicating, and reasoning over unstructured web pages. That's GPU time and API calls spent reconstructing what the business already knows. Pre-structured authoritative data eliminates most of that compute.
What AITWIRE provides
Canonical facts API
AITWIRE businesses publish governed canonical facts — pricing, services, contact details, descriptions, policies — as versioned, timestamped data that AI systems can crawl or integrate with.
JSON-LD structured data
AITWIRE publishes Organization, Product, Service, FAQ, and LocalBusiness JSON-LD on hosted authority pages so crawlers get machine-readable data in formats they already understand.
llms.txt and feeds
AITWIRE generates llms.txt, RSS, sitemaps, and structured feeds that point AI crawlers toward current facts and content. AITWIRE measures whether engines retrieve and cite those surfaces.
Entity lookup API
Resolve a business by domain, name, or identifier and get structured identity data, canonical facts, and verified claims — useful for systems that choose to integrate directly.
AI crawler directives
AITWIRE configures crawler access policies so businesses can allow training and citation crawlers, or block specific bots. The current default favors presence in AI answers while retaining tenant control.
Governance rules and constraints
Businesses can publish rules and context about how their information should be used. AITWIRE exposes the policy layer and records enforcement decisions for auditability.
Change signals and recrawl hints
When canonical facts or authority surfaces change, AITWIRE can issue recrawl signals such as IndexNow and update dynamic feeds so engines can discover fresh content faster.
Measurement and conformance
AITWIRE measures how AI systems actually describe, cite, and recommend a business, separating proven analytics from experimental retrieval-attribution proof.
Reduce retrieval ambiguity
Structured canonical facts can reduce ambiguity for systems that crawl or integrate with them. AITWIRE does not assume engines will use the data — it measures adoption and impact.
Web Intelligence Index
AITWIRE proactively crawls the web to build entity profiles for businesses that haven't yet claimed their account — identifying conflicting data across directories, social platforms, and AI outputs. Your AI gets a conflict-aware data layer: authoritative facts where businesses manage them, and flagged inconsistencies where they don't.
Build on current business facts
A verified, conflict-aware, governance-enriched data layer — authoritative facts where businesses manage them, and measurement where AI systems still need to prove adoption.