AI Maturity
AI Maturity measures how deeply artificial intelligence capabilities appear to be integrated into a companyโs digital presence, infrastructure, products, or workflows.
A high AI Maturity score generally indicates that a website or business has moved beyond basic experimentation and has implemented structured AI-related systems, developer tooling, automation, machine-readable documentation, or agent-accessible resources.
Signals may include:
Public AI-related documentation
Structured machine-readable resources
AI-focused developer infrastructure
Agent-oriented integrations
Automation and workflow exposure
AI product positioning or AI-enabled services
A low AI Maturity score does not necessarily mean a company is not using AI internally. It simply means there is limited public evidence of mature AI integration visible from the outside.
AI Openness
AI Openness measures how accessible and welcoming a website is to automated systems, AI agents, crawlers, and machine-to-machine interaction.
A high AI Openness score suggests that a website allows AI systems to discover, read, and interact with publicly available resources with minimal restrictions.
Signals may include:
Publicly accessible machine-readable content
Clear discovery endpoints
Accessible developer documentation
Minimal blocking of automated systems
Limited use of aggressive anti-bot protections
A lower AI Openness score may indicate that the site restricts automated access through technical controls, access challenges, or explicit limitations placed on AI crawlers and automated agents.
AI Openness is not a judgment of security quality. Many organizations intentionally restrict automated access for security, compliance, or intellectual property reasons.
Agent Readiness
Agent Readiness measures how prepared a website or platform is for direct interaction with AI agents, automation tools, and autonomous software systems.
A high Agent Readiness score indicates that systems appear structured in a way that allows AI agents to:
Discover capabilities
Understand available actions
Access machine-readable interfaces
Interact programmatically
Navigate workflows without human interpretation
Signals may include:
Structured APIs
Machine-readable specifications
Agent-oriented endpoints
Developer accessibility
Automated workflow support
Public integration infrastructure
Agent Readiness focuses on operational usability for AI systems rather than general AI adoption.
A company may have strong internal AI usage but low Agent Readiness if its systems are not externally accessible to autonomous software.
AI Visibility
AI Visibility measures how visible and externally identifiable AI-related technologies, products, services, or infrastructure are across a websiteโs public footprint.
A high AI Visibility score generally indicates that AI-related systems are publicly exposed, referenced, or discoverable through visible technologies, content, integrations, or infrastructure.
Signals may include:
Public AI product references
AI-enabled features
AI-focused integrations
AI-related developer tooling
Machine-readable AI resources
Public technical indicators of AI usage
AI Visibility is designed to measure observable presence, not sophistication.
A business may have advanced internal AI systems while maintaining low AI Visibility if those systems are intentionally hidden from public view.