Systems, ownership, connected tools and qualified consequential paths.
Visibility → accountable scopeKnow your AI.
Prove its boundaries.
Discover what connected AI systems can reach. Evaluate security and delegated authority. Support accountable decisions, monitoring and inspectable evidence.
Know the AI estate.
Which agents, tools and consequences can your organization actually see?
AI estate & ownership
Connect systems, owners, models and declared inventory.
Registered and discovered sources are not automatically verified.
Explore this capabilityGo deeper. Stay focused on value.
Explore the complete feature families behind each capability and the work product they contribute. Select any capability or feature to change the explanation and diagram.
Know the AI estate.
Which agents, tools and consequences can your organization actually see?
Reveal consequential paths, ownership and visibility gaps before expanding AI autonomy.
AI estate & ownership
Connect systems, owners, models and declared inventory.
Across the connected AI environment.
HAIEC brings supported sources into a shared operating picture, while distinguishing proven facts from the unknown.
Coverage describes assessment surfaces, not a claim that all ten are integrated or observed for every customer.
What AI can do. What it was allowed. What evidence proves.
A model score, a security scanner, a permission and a business policy tell different parts of the story. HAIEC compares five independent evidence perspectives without turning unknowns into passes.
Requested
What the task or actor sought to do. A qualified source establishes only what its provenance, scope and available records support.
Nine dimensions of authority.
DAI compares delegated authority within bounded operational dimensions. These are analytical dimensions, not additional evidence planes.
Not just features. Work your teams can use.
Technical findings become reviewable artifacts for engineering, security, risk, executives and auditors.
Selected technical tests, delegated authority comparisons and explicit evidence gaps.
Analysis → prioritized actionApplicable obligations, framework crosswalks and accountable evidence reviewers.
Requirements → reviewable evidenceVersioned operating boundaries, approvers, exceptions and conditions.
Findings → human decisionsSource health, qualified change signals and reconstructable timelines where connected.
Changes → investigation contextMaster Assurance Report, Agent Audit, evidence packages and stated limitations.
Evidence → inspectable assuranceSupporting products and research methods, not additional platform assurance engines.
Clarity for every accountable team.
One qualified evidence foundation, tailored to the decisions different enterprise owners need to make.
See the real AI estate.
Connected systems, consequential reachability, integration status and technical ownership.
Prioritize actionable exposure.
Vulnerabilities, delegated authority gaps and controls evaluated against possible effects.
Review qualified proof.
Obligation mapping, evidence lineage, review ownership and explicitly unresolved questions.
Enable accountable autonomy.
Better-informed release, investment and operating decisions using bounded evidence.
One platform. High assurance in every consequence.
Start with a consequential AI question, connect the relevant sources and expand what the evidence can establish.