Enterprise AI is distributed across far more than production models. It includes third-party tools, autonomous agents, embedded application features, employee-used services, datasets, APIs, developer environments, pilot projects, and systems still undergoing assessment or remediation.
When this information is spread across spreadsheets, procurement records, security tools, development platforms, and business teams, organisations cannot maintain a reliable view of their AI estate.
An annual survey or spreadsheet becomes outdated as soon as the environment changes. It may record that an asset exists, but not whether it remains approved, what data it now accesses, what it costs, whether controls are operating, or who is accountable for it.
Veranthios maintains a live governance record that follows each asset throughout its lifecycle and preserves the evidence behind every material decision.
AI now operates across employee tools, developer environments, SaaS platforms, embedded features, third-party vendors, and autonomous agents. Without continuous exposure management, organisations cannot reliably see what AI is running, what data and systems it can access, what it costs, or whether appropriate ownership and controls are in place.
Traditional governance programmes often depend on questionnaires, spreadsheets, policy documents, and periodic reviews. Veranthios creates a continuously updated operational record of AI activity, ownership, exposure, cost, controls, decisions, and evidence across the enterprise.
Veranthios converts live governance activity into defensible evidence, including AI inventories, ownership records, risk assessments, approvals, control status, remediation activity, and audit trails. This gives boards, auditors, regulators, and customers a clearer view of enterprise AI exposure.
AI does not operate only through formally approved models. It also appears through embedded SaaS features, employee tools, autonomous agents, developer workflows, third-party services, datasets, and experimental projects. Veranthios brings these assets into a single, continuously updated registry—giving governance teams a live view of what is operating, where it is deployed, who owns it, and what systems or data it can access.
Maintain an up-to-date record of models, agents, datasets, embedded AI features, third-party tools, pilots, and production systems.
Connect every asset to its business owner, technical owner, purpose, environment, users, integrations, and affected data.
A static list cannot govern AI. Each asset must be assessed, assigned accountable ownership, classified by risk, and managed throughout its lifecycle. Veranthios helps organisations track approval status, business purpose, regulatory relevance, data sensitivity, deployment stage, control requirements, remediation actions, and ongoing cost—ensuring that every AI asset has a clear governance path.
Track assets from discovery and assessment through approval, deployment, monitoring, remediation, retirement, or rejection.
Prioritise assets according to exposure, regulatory impact, business criticality, data sensitivity, ownership gaps, and financial cost.
Boards, auditors, regulators, and enterprise customers increasingly expect organisations to show what AI is operating, who approved it, what data it can access, what risks were identified, and what controls are in place. Veranthios preserves this information in a tamper-evident system of record, connecting each AI asset to its assessments, ownership, decisions, remediation history, supporting documentation, and current governance status.
Maintain dated evidence of ownership, assessments, approvals, control decisions, exceptions, and remediation activity.
Generate defensible reporting across the organisation without rebuilding evidence from spreadsheets, surveys, and disconnected systems.