Overview
AssetUno AI is an enterprise AI asset management and governance platform that helps organizations discover which AI services are being used, identify Shadow AI, measure usage and cost, connect activity with organizational context, and govern AI assets through a structured registry, risk and action model.
The platform brings together AI APIs, coding assistants, enterprise AI workspaces, security evidence and identity context in one provider-independent management layer. Instead of managing AI usage through separate invoices, provider portals, spreadsheets and security tools, AssetUno AI consolidates technical and management evidence into a common view of what AI is being used, by whom, at what cost, under which ownership and approval status, and where governance action is required.
From a business perspective, AssetUno AI improves visibility and accountability across enterprise AI investments. It helps organizations identify unmanaged AI adoption, understand licensed and actual usage, allocate AI spend to teams and business context, evaluate value and adoption, and prioritize optimization or governance actions. The platform complements existing ITAM, SAM, FinOps, security and governance processes by providing an AI-specific management layer.
Important functions include:
Shadow AI Discovery identifies unmanaged or insufficiently governed AI usage from connected evidence sources and presents observed AI services, approval status, organizational context, data exposure information and supporting evidence. Shadow AI is a dedicated primary product domain rather than only a governance report.
AI Landscape and Registry provide a structured inventory of AI providers, services, models and related organizational context. AI Governance combines the AI Registry with risk and trust evidence, policies, exceptions, owners and remediation actions.
Usage & Cost Optimization consolidates provider-native usage, token, request, credit, license and cost information while preserving available source detail. Usage and spend can be attributed to users, teams, departments, cost centers, projects and repositories to support ownership, budgeting and optimization decisions.
Value Realization connects AI usage and adoption with customer-defined business or engineering outcome indicators, allowing organizations to evaluate AI investment beyond cost alone.
AI Governance and Risk Management combine Shadow AI findings, data-exposure evidence, policy context and AI Registry information with risk workflows. Findings can be assigned to owners, linked to actions, managed with due dates and decision notes, or handled through controlled exceptions and accepted-risk states.
AI-assisted Analysis and Governance Hints use measured AssetUno evidence to identify governance priorities and recommend actions across areas such as policy violations, sensitive-data exposure, Shadow AI risk, spend concentration, license utilization and data quality. AI-assisted narrative analysis is separated from the underlying evidence-based recommendations.
Typical use cases:
- Discover Shadow AI and identify AI services being used outside approved ownership, procurement or governance processes.
- Build and maintain an enterprise inventory of AI services and models with ownership, approval and governance context.
- Analyze token, request, license, adoption and cost data across multiple AI providers and allocate spend to organizational units.
- Identify governance risks, data-exposure signals, policy gaps and unmanaged AI usage and assign remediation actions to responsible owners.
- Compare AI cost and adoption with business or engineering outcomes to support license optimization, budget allocation and investment decisions.
Operating concept:
AssetUno AI follows a Collect, Normalize, Attribute, Compare and Act operating model. Provider, security and identity evidence is collected through controlled connectors, normalized without discarding provider-specific metrics, attributed to organizational context, compared across cost, adoption, value and governance dimensions, and converted into optimization or governance actions.
Reporting and Dashboard Options:
AssetUno AI provides an Executive Overview together with dedicated views for Shadow AI, Usage & Cost, Value Realization, AI Governance and Insights & Reports. Dashboards provide visibility into the AI landscape, active users, spend, provider and model usage, token and request volumes, Shadow AI findings, governance risks, actions, exceptions and organizational attribution. Evidence-based reports support management review, operational follow-up and export to broader BI, ITAM and governance processes.
Benefits
Integration
AssetUno AI integrates with supported AI providers, security and identity platforms through configurable connectors and controlled data-import workflows. It consolidates provider usage, cost, license, identity and governance evidence into a common data model for further analysis and processing.
Supported integrations cover AI platforms, security and DLP systems, and identity sources used for Shadow AI discovery, ownership attribution, risk analysis and governance context.
AssetUno AI provides structured CSV/XLSX exports and API-based data exchange for integration with BI, ITAM, SAM, FinOps, governance and other enterprise management processes. Connector mappings, organizational dimensions and data-processing workflows can be configured according to the target system and customer data model.
No specific dependency on USU Service Management is required. AssetUno AI can complement USU and other enterprise management environments by supplying normalized AI usage, cost, Shadow AI, risk and governance data for downstream processes.