Platform / AI asset inventory

AI Asset Inventory

One inventory across every AI surface your enterprise runs in production. Auto-discovered where the data source allows it, customer-declared where it does not, scored continuously.

Last reviewed June 2026

Problem

The gap AI asset inventory closes

AI assets accumulate faster than the CMDB tracks them. Shadow LLM apps, undocumented MCP servers, and orphan RAG pipelines turn into the first vulnerabilities an auditor finds. Security cannot govern what it cannot see.

How Penaxtra approaches it

How Penaxtra delivers AI asset inventory

Penaxtra catalogues 11 AI asset kinds today in a single workspace. Each row links the asset to its scans, findings, framework mappings, and risk score. Auto-pull integrations cover managed and self-hosted vector stores, fine-tune providers, and self-hosted model registries. Managed foundation-model and ML platform services across the major cloud providers auto-discover via read-only role.

Technical capabilities

AI asset inventory capabilities

11 AI asset kinds today, each with a typed schema and risk score

Auto-pull integrations for vector databases and fine-tune providers

Cloud AI service auto-discovery via read-only role

AI Application grouping: bundle endpoints + agents + RAG + tools as a single risk-owned unit

Hygiene score: verified + reported within seven days share

CSV and JSON export of the full inventory

API endpoints for asset CRUD + tagging

Compliance mapping

AI asset inventory compliance mapping

Asset inventory satisfies NIST AI 600-1 MAP-1, ISO/IEC 42001 Annex A.6 (AI asset management), EU AI Act Article 17 (quality management system), and supports the AI-BOM expectation in OWASP Agentic Top 10.

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