Updated Weekly

AI Bill of Materials Registry

Structured AIBOM dataset for 3,400+ AI models with SPDX licensing, EU AI Act risk classification, safety evaluations, and procurement metadata. Machine-readable, multi-standard, open-source.

What This Registry Covers

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SPDX License Normalization

Every model mapped to standardized SPDX identifiers with commercial use rights, modification permissions, and distribution terms.

EU AI Act Risk Tiers

Automated classification into Unacceptable, High, Limited, and Minimal risk tiers per EU AI Act regulatory framework.

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Safety Evaluations

541 models with red-teaming results, bias evaluations, and content filtering capabilities. Explicit flags when safety data is absent.

Multi-Standard Alignment

Records map to SPDX 3.0 AI Profile, CycloneDX ML, and NTIA SBOM minimum elements for procurement-ready compliance.

Beyond Raw Model Metadata

The AIBOM Registry is not repackaged upstream data. Our pipeline extracts raw model information and applies enrichment layers that do not exist in any single source: license normalization, regulatory risk classification, 10-dimension quality scoring, cross-provider schema unification, and procurement-ready formats.

3,400+AI Models
45+Providers
19Task Categories
85%Avg Completeness

Quality Tiers

Every model receives a 10-dimension weighted completeness score covering identity, licensing, training provenance, safety, and compliance. Models are tiered Gold, Silver, or Bronze based on their score.

2,988Gold Tier
471Silver Tier
86%License Coverage
WeeklyRefresh Cycle

Use Cases

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Enterprise Procurement

Structured metadata for vendor evaluation, license auditing, and supply chain risk assessment across your AI model stack.

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Regulatory Compliance

EU AI Act documentation, NIST AI RMF alignment, and NTIA SBOM minimum elements for audit-ready reporting.

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Security Research

Centralized access to safety evaluations, red-teaming results, and vulnerability metadata across thousands of models.

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Data Products

Available on AWS Data Exchange. JSON, CSV, and Parquet formats with versioned schema guarantees for downstream integration.

Methodology

Data is collected weekly via automated pipelines from model registries, official documentation, and public APIs. Each record undergoes SPDX normalization, EU AI Act risk classification, and 10-dimension quality scoring. All collection scripts are open-source and auditable in the GitHub repository.