Centralized registry of all your AI assets
Gain full-spectrum visibility over your AI use cases with a unified, continuously updated inventory.
Get a demoAI systems are scattered across the organization, with little to no visibility.
- AI systems span models, applications, APIs and embedded components – often without clear ownership or documentation.
Mapping AI is inherently complex
- AI adoption is accelerating across business units, outpacing the ability to track and oversee deployments.
Use cases are scaling faster than governance
- Unmonitored tools and unsanctioned AI usage introduce hidden risks across the enterprise.
Shadow AI is on the rise
An observatory of your AI assets
The Naaia platform embeds a comprehensive inventory capability designed to centralize all your AI assets, across models, systems, components, and generative AI (or not) use cases.
Whether through manual input or seamless integrations with your existing IT ecosystem, Naaia enables you to consolidate and structure your entire AI landscape into a single, authoritative registry.
Ensure you’re always up-to-date
Naaia allows you to enrich each AI asset with key operational data, including the countries where it is developed, deployed, or distributed.
As regulatory frameworks evolve across jurisdictions, Naaia dynamically maps applicable requirements to your inventory—ensuring that compliance obligations are continuously aligned with your actual AI use cases, without manual rework.
Native Connector with Wiz
Naaia integrates natively with Wiz to bridge AI governance and cloud security signals.
By ingesting insights from Wiz, Naaia enhances your inventory with real-time risk indicators, misconfiguration alerts, and exposure signals, bringing security context directly into your AI governance workflows.
This integration enables a more proactive and unified approach to managing AI risk across your infrastructure.
With Naaia
Establish a single source of truth
Register all your AI products (AI systems, models, components) within the Naaia platform.
Aggregate and structure all asset metadata into a single, reliable registry
Bring together critical information related to your AI assets in a unified registry to support governance, traceability, and compliance.
Orchestrate governance at scale
Industrialize your AI governance processes across business units, entities, and geographies.
Centralize oversight at the group level while preserving entity-level granularity
Ensure centralized oversight of your AI ecosystem while preserving precise tracking of local assets, ownership, and responsibilities.
Trusted by those who build with AI
Naaia enabled us to move toward a more value-driven approach to AI governance. Beyond compliance, the platform helps us prioritize AI initiatives based on business impact, risk, and strategic value.
Colas naturally selected Naaia for its intuitive user experience, as well as its educational and thought-leadership approach to simplifying complex AI topics. A truly collaborative framework was established throughout the project, driving stronger team engagement, seamless adoption, and operational efficiency.
We chose Naaia for its clear framework to inventory and govern our AI initiatives. We particularly appreciate the combination of its user-friendly tools, which make compliance more accessible, and the supportive guidance from their team.
Naaia helped us operationalize AI Act readiness across our regional authority’s services with a clear and trusted governance framework. The platform improved collaboration between departments and gave us the visibility needed to scale AI responsibly.
Learn about other capabilities
Frequently asked questions
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What is an AI asset inventory, and why does the EU AI Act require one?
An AI asset inventory is a structured register of all AI systems an organization develops, deploys, or uses — documenting each system’s purpose, risk classification, technical specifications, provider, and oversight responsibilities. The EU AI Act makes such an inventory a practical necessity for high-risk AI system operators: without knowing exactly which systems are in scope, organizations cannot fulfill obligations around risk management, transparency, post-market surveillance, or incident reporting. An accurate inventory is the foundation of any credible AI governance program.
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How can organizations detect and inventory shadow AI systems used across departments?
Shadow AI — tools adopted by teams without central IT or governance oversight — has become one of the most significant compliance risks in 2026. Detection requires a combination of network-level scanning (identifying API calls to known AI services), survey-based self-reporting by department heads, integration with procurement and expense management systems (to catch SaaS subscriptions), and regular process audits. Once identified, each system must be assessed against the organization’s AI risk classification framework and either formally approved, restricted, or prohibited.
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What are the regulatory and operational risks of not maintaining an AI system inventory in 2026?
Organizations without an AI system inventory face significant risks on two fronts. Regulatory: under the EU AI Act, failure to maintain required documentation for high-risk AI systems can result in fines of up to €15 million or 3% of global annual turnover. Operational: untracked AI systems create liability exposure for biased decisions, data breaches originating from AI-processed data, and reputational damage from incidents that cannot be traced or explained. In 2026, the inability to demonstrate governance is increasingly treated as evidence of organizational negligence.
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What information must an AI register contain to satisfy EU AI Act compliance requirements?
For high-risk AI systems, the EU AI Act requires the register to include: a general description of the system and its intended purpose, the risk classification and justification, technical documentation (architecture, training data, performance metrics), information on the provider and any third-party components, the human oversight measures in place, post-market monitoring procedures, and incident reporting history. For general-purpose AI (GPAI) models, additional transparency obligations apply. Registers must be maintained in a format shareable with national competent authorities upon request.