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Regulated AI Navigator

Turn an AI use case into its full regulatory footprint — every domain it touches, from AI law and data protection to cyber, product safety and sector rules — with the obligations, the architecture and the evidence you owe, in about two minutes.

Community-curated knowledge graph — every claim carries its citation across law, engineering and governance. Every change traceable →

Start where you stand →Browse 78 profiles

Where do you stand? › Route 3 · Vendors & stack

I know which systems I need — who supplies them?

Pick the components you have to put in place. For each one you get the build-vs-buy reading and the market layer that supplies it, with the same scored recommendations and confidence the full analysis uses. Nothing is stored; the selection lives in the URL.

Target market(s)European UnionUnited States (federal)change

Legally-driven components are flagged when their requiring regulation sits outside your selected markets.

Target market(s)

Where will this system be used or placed on the market? The conclusion is derived for these jurisdictions — instruments that bind only elsewhere are left out.

Europe
North America
Latin America
Asia-Pacific
Middle East
Africa

Selected: European Union, United States (federal) · thin-coverage jurisdictions need verification

density

Step 1 of 2 — pick your components3 selected

Document Intelligence EngineAI Register & Model Registry / FactsheetsWORM / Immutable Audit Vault
Two-Tier Air-Gapped De-Identification Ingestion (3)
Deterministic Circuit Breaker with Reversible Shadow Execution (3)
Grounded Citational RAG (5)
Deterministic Document-Validation Pipeline (3)
Dual-Agent Guardian Topology (4)
Hardened Edge / IoT Pattern (3)
Constrained GAM with Differential-Privacy Tokenisation (2)
Glass-Box EBM with Monotonic Constraints (2)
Guarded RAG Pattern (2)
Human-in-the-Loop Core Pattern (1)
Tiered-Confidence Moderation Queue (1)
Agentic RDA Stack (6 Layers) (3)
Sandboxed Execution with SAST Gates (1)
Sovereign Resilient Enterprise Pattern (5)
Four-Layer TRiSM Enterprise Stack (2)
Cross-cutting components (22)

Step 2 of 2 — the vendor & stack view

3 of 3 selected components are covered by 6 market layers.

Named vendors are community-maintained, disputable examples — not an endorsement. The stable object is the market layer. Compare with the reference stack for your regulatory profile →

Build or buy, per component (3)

AI Register & Model Registry / Factsheets buy (products exist) KRJPCNVNUS-NY
A AI GRC & Governance Platforms / Agent Observability & Model Risk Management / Public Transparency Registers & System Cards product can carry this; the buyer's duties stay with you.
Required by: AI Framework Act (KR), AI Promotion Act (JP), Algorithmic Recommendation Provisions (CN), Law on Digital Technology Industry (VN), New York RAISE Act, Standalone AI Law (VN) in forcein forcein forcein forceenacted — not yet applicablein force
Legally required in KR, JP, CN, VN, US-NY — none of your selected markets carry this driver; treat it as a market-specific requirement, not a universal one. Help verify coverage →
Document Intelligence Engine buy (products exist)
A Grounding, Retrieval & Agent Memory / Agentic Applications & Copilots product can carry this; the buyer's duties stay with you.
WORM / Immutable Audit Vault buy (products exist) EUDEthinUS
A Cryptographic Evidence & Audit Ledger product can carry this; the buyer's duties stay with you.
Required by: AI Liability Directive (withdrawn), BaFin MaRisk (Mindestanforderungen an das Risikomanagement), Bank Secrecy Act / FinCEN Program Rules, FINRA Rule 4511 (General Books & Records), Revised Product Liability Directive, SEC Rule 17a-4 (US Records Retention) withdrawn — no longer lawin forcein forcein forcein forcein force
Legally required in EU, US (your selected markets); also required in DE, which you have not selected. Help verify coverage →

Public Transparency Registers & System Cards — covers 1 of your components

Covers: AI Register & Model Registry / Factsheets. This layer supplies 2 components in the graph.
Confidence: strong (70/100)
Community-maintained examples
Saidot
Filters to self-hostable, customer-VPC and open-source options when personal or confidential data cannot leave the EU.
ExampleSub-categoryWhat it doesHostingClaimed alignments
Saidotpublic AI registerAI register with published system cards and regulation-mapped documentation workflows. Typical: public AI register, system cards. Scope overlap: Its documentation and register scope overlaps this platform's own; we have a commercial interest in the comparison.SaaS (vendor cloud)EU AI Act documentation positioningISO 42001 alignment (claimed)

Community-maintained, disputable examples — not an endorsement and not a ranking. Alignments are as claimed by vendors or the source compilation, not verified by RAIN; a certification is shown as a certification only where a certificate or registry reference is recorded.

Disclosure: RAI·N·avigator operates in this category too, so we have a commercial interest in any comparison here. That is why this layer maps product classes to control objectives and lists named products as community-maintained examples — we publish no rankings, no quadrants and no coverage assertions about any vendor, including ourselves.

Select on
Versioning of published statements against the system version they describe; whether a card is generated from your governance record or re-authored by hand; language coverage and accessibility of the published surface; export and self-hosting of the public register; whether unpublishing leaves an auditable trail.
Why this confidence
  • 1 in-scope component of this use case is supplied by this layer (AI Register & Model Registry / Factsheets) — a direct supplied_by path in the graph.
  • This layer's graph purpose overlaps strongly with your scope (1 of 2 components it supplies are in scope).
  • The catalog use-case match is strong, so the component set this layer was derived from is reliable.
  • High-risk tier: this layer carries mandatory Chapter III duties, so some tooling in it is non-optional.
  • 1 community-maintained example vendor recorded on the layer node.
  • Selection metrics for this layer are documented, so the shortlist can be compared objectively.
Alternatives
  • Cryptographic Evidence & Audit Ledger — confidence moderate (68/100, -2 vs. this layer); also covers: WORM / Immutable Audit Vault
  • Agentic Applications & Copilots — confidence moderate (67/100, -3 vs. this layer); also covers: Document Intelligence Engine

Cryptographic Evidence & Audit Ledger — covers 1 of your components

Covers: WORM / Immutable Audit Vault. This layer supplies 3 components in the graph.
Confidence: moderate (68/100)
Community-maintained examples
Fact0 · Traccia
Filters to self-hostable, customer-VPC and open-source options when personal or confidential data cannot leave the EU.
ExampleSub-categoryWhat it doesHostingClaimed alignments
Fact0cryptographic evidence ledgerPositions itself as a tamper-evident ledger for AI decision records. Typical: decision records, audit trail.not checkedsupports Art. 12 record-keeping (claimed)
Tracciaaudit trail & traceabilityPositions itself around traceability of AI pipeline steps and artefacts. Typical: traceability, artifact lineage.not checkedsupports Art. 12 record-keeping (claimed)

Community-maintained, disputable examples — not an endorsement and not a ranking. Alignments are as claimed by vendors or the source compilation, not verified by RAIN; a certification is shown as a certification only where a certificate or registry reference is recorded.

Disclosure: RAI·N·avigator operates in this category too, so we have a commercial interest in any comparison here. That is why this layer maps product classes to control objectives and lists named products as community-maintained examples — we publish no rankings, no quadrants and no coverage assertions about any vendor, including ourselves.

Select on
Append-only guarantees and who can rotate or delete (including the vendor); anchoring mechanism (qualified timestamp, transparency log, notarisation) and whether verification works without the vendor; retention and export in a readable format at end of contract; throughput and cost at your event volume.
Why this confidence
  • 1 in-scope component of this use case is supplied by this layer (WORM / Immutable Audit Vault) — a direct supplied_by path in the graph.
  • The catalog use-case match is strong, so the component set this layer was derived from is reliable.
  • High-risk tier: this layer carries mandatory Chapter III duties, so some tooling in it is non-optional.
  • 2 community-maintained example vendors recorded on the layer node.
  • Selection metrics for this layer are documented, so the shortlist can be compared objectively.
  • Only 1 of 3 components this layer supplies are in your scope — evaluate a narrow subset of its capabilities.
Alternatives
  • Public Transparency Registers & System Cards — confidence strong (70/100, +2 vs. this layer); also covers: AI Register & Model Registry / Factsheets
  • Agentic Applications & Copilots — confidence moderate (67/100, -1 vs. this layer); also covers: Document Intelligence Engine

Agentic Applications & Copilots — covers 1 of your components

Covers: Document Intelligence Engine. This layer supplies 4 components in the graph.
Confidence: moderate (67/100)
Community-maintained examples
GitHub Copilot · Microsoft 365 Copilot · Perplexity Enterprise · Cursor · Dropzone AI · Devin (Cognition) · Vanta · Fin (Intercom) · SAP
Filters to self-hostable, customer-VPC and open-source options when personal or confidential data cannot leave the EU.
ExampleSub-categoryWhat it doesHostingClaimed alignments
GitHub Copilotdeveloper copilotCode completion and agent modes inside the IDE and repository workflow. Typical: software engineering, code review.not checkedSOC 2 (claimed)enterprise data-handling commitments (claimed)
Microsoft 365 Copilotproductivity copilotAssistant across mail, documents and meetings inheriting existing tenant permissions. Typical: knowledge work, meeting summaries.not checkedISO 27001 (claimed)SOC 2 (claimed)EU data-boundary positioning
Perplexity Enterpriseresearch assistantCited web and internal search with source attribution per answer. Typical: market research, citation-backed search.not checkedSOC 2 (claimed)enterprise data-handling commitments (claimed)
Cursordeveloper copilotAI-native editor with repository-wide agent edits. Typical: software engineering, refactoring.not checkedSOC 2 (claimed)privacy-mode option (claimed)
Dropzone AIsecurity operations agentAutonomous triage of security alerts with written investigation records. Typical: SOC triage, incident write-ups.not checkedSOC 2 (claimed)
Devin (Cognition)autonomous software agentLong-running software agent taking tickets to pull requests. Typical: software engineering, backlog automation.not checkedvendor-stated security posture
Vantacompliance automationContinuous control monitoring and evidence collection across frameworks. Typical: evidence automation, audit readiness.not checkedSOC 2 (claimed)ISO 27001/42001 evidence workflows (claimed)
Fin (Intercom)customer-service agentResolution-priced support agent answering from your help content. Typical: customer support, deflection.not checkedSOC 2 (claimed)GDPR-positioned
SAPembedded enterprise AIAI features and agents embedded in ERP, HR and procurement suites, governed through the vendor's own AI platform layer. Typical: embedded HR AI, procurement automation, finance automation.SaaS (vendor cloud)ISO/IEC 42001 certification claim (claimed)EU AI Act readiness positioning

Community-maintained, disputable examples — not an endorsement and not a ranking. Alignments are as claimed by vendors or the source compilation, not verified by RAIN; a certification is shown as a certification only where a certificate or registry reference is recorded.

Disclosure: RAI·N·avigator operates in this category too, so we have a commercial interest in any comparison here. That is why this layer maps product classes to control objectives and lists named products as community-maintained examples — we publish no rankings, no quadrants and no coverage assertions about any vendor, including ourselves.

Select on
Permission model and identity scoping; audit log export; tenant data-handling and retention terms; deployer-duty support (disclosure, oversight, incident reporting); outcome pricing vs seat pricing.
Why this confidence
  • 1 in-scope component of this use case is supplied by this layer (Document Intelligence Engine) — a direct supplied_by path in the graph.
  • The catalog use-case match is strong, so the component set this layer was derived from is reliable.
  • High-risk tier: this layer carries mandatory Chapter III duties, so some tooling in it is non-optional.
  • 9 community-maintained example vendors recorded on the layer node.
  • Selection metrics for this layer are documented, so the shortlist can be compared objectively.
  • Only 1 of 4 components this layer supplies are in your scope — evaluate a narrow subset of its capabilities.
Alternatives
  • Public Transparency Registers & System Cards — confidence strong (70/100, +3 vs. this layer); also covers: AI Register & Model Registry / Factsheets
  • Cryptographic Evidence & Audit Ledger — confidence moderate (68/100, +1 vs. this layer); also covers: WORM / Immutable Audit Vault

AI GRC & Governance Platforms — covers 1 of your components

Covers: AI Register & Model Registry / Factsheets. This layer supplies 7 components in the graph.
Confidence: moderate (66/100)
Community-maintained examples
Credo AI · ModelOp · Holistic AI · IBM watsonx.governance · OneTrust · ServiceNow · Monitaur
Filters to self-hostable, customer-VPC and open-source options when personal or confidential data cannot leave the EU.
ExampleSub-categoryWhat it doesHostingClaimed alignments
Credo AIAI governance platformPolicy packs, risk tiering and evidence workflows mapped across frameworks. Typical: AI registry, policy administration. Scope overlap: Its scope overlaps this platform's own; we have a commercial interest in the comparison.not checkedISO 42001 alignment (claimed)EU AI Act readiness positioning
Holistic AIAI governance & auditRisk assessment, bias auditing and regulatory reporting workflows. Typical: bias audit, regulatory reporting. Scope overlap: Its scope overlaps this platform's own; we have a commercial interest in the comparison.not checkedNYC LL144 audit support (claimed)EU AI Act readiness positioning
IBM watsonx.governanceAI governance platformGovernance, factsheets and monitoring integrated with the IBM stack. Typical: factsheets, model monitoring. Scope overlap: Its scope overlaps this platform's own; we have a commercial interest in the comparison.not checkedISO 42001 alignment (claimed)Art. 11 documentation support (claimed)
ModelOpAI/model governanceModel and agent inventory with automated lifecycle controls for large estates. Typical: model inventory, control automation. Scope overlap: Its scope overlaps this platform's own; we have a commercial interest in the comparison.not checkedmodel-risk positioning (SR 11-7 style, claimed)ISO 42001 alignment (claimed)
Monitaurinsurance & lending model governanceModel governance and documentation aimed at insurance and lending supervision. Typical: insurance underwriting, credit decisioning. Scope overlap: Its model-governance scope overlaps this platform's own; we have a commercial interest in the comparison.SaaS (vendor cloud)NAIC model-governance positioning (claimed)SR 11-7 practice alignment (claimed)
OneTrustGRC & privacy platformPrivacy and AI governance modules extending an existing GRC system of record. Typical: DPIA/FRIA workflow, policy management. Scope overlap: Its scope overlaps this platform's own; we have a commercial interest in the comparison.not checkedISO 27001 (claimed)GDPR-positioned
ServiceNowintake & ITSM workflowUse-case intake, approval workflow and risk records inside an existing ITSM estate. Typical: AI intake, policy administration. Scope overlap: Its AI-governance module overlaps this platform's own scope; we have a commercial interest in the comparison.SaaS (vendor cloud)ISO 42001 alignment (claimed)EU AI Act readiness positioning

Community-maintained, disputable examples — not an endorsement and not a ranking. Alignments are as claimed by vendors or the source compilation, not verified by RAIN; a certification is shown as a certification only where a certificate or registry reference is recorded.

Disclosure: RAI·N·avigator operates in this category too, so we have a commercial interest in any comparison here. That is why this layer maps product classes to control objectives and lists named products as community-maintained examples — we publish no rankings, no quadrants and no coverage assertions about any vendor, including ourselves.

Select on
multi-model/multi-cloud cataloging incl. third-party SaaS, automated risk tiering, regulatory reporting, independent-2nd-line deployability, cross-framework control deduplication
Why this confidence
  • 1 in-scope component of this use case is supplied by this layer (AI Register & Model Registry / Factsheets) — a direct supplied_by path in the graph.
  • The catalog use-case match is strong, so the component set this layer was derived from is reliable.
  • High-risk tier: this layer carries mandatory Chapter III duties, so some tooling in it is non-optional.
  • 7 community-maintained example vendors recorded on the layer node.
  • Selection metrics for this layer are documented, so the shortlist can be compared objectively.
  • Only 1 of 7 components this layer supplies are in your scope — evaluate a narrow subset of its capabilities.
Alternatives
  • Public Transparency Registers & System Cards — confidence strong (70/100, +4 vs. this layer); overlapping coverage, no additional selected component
  • Cryptographic Evidence & Audit Ledger — confidence moderate (68/100, +2 vs. this layer); also covers: WORM / Immutable Audit Vault

Grounding, Retrieval & Agent Memory — covers 1 of your components

Covers: Document Intelligence Engine. This layer supplies 8 components in the graph.
Confidence: moderate (66/100)
Community-maintained examples
Docling · LlamaParse · Amazon Textract · Diffbot · Firecrawl · Voyage AI · Nomic · Pinecone · Weaviate · Qdrant · Milvus · pgvector · Letta (MemGPT) · Mem0 · Zep · Cognee
Filters to self-hostable, customer-VPC and open-source options when personal or confidential data cannot leave the EU.
ExampleSub-categoryWhat it doesHostingClaimed alignments
Doclingdocument parserOpen-source layout-aware parsing of PDFs and office formats into structured chunks. Typical: RAG ingestion, air-gapped pipelines.self-hostableEU sovereignty positioning
LlamaParsedocument parserManaged parsing service tuned for tables and complex documents feeding RAG. Typical: RAG ingestion, table extraction.not checkedSOC 2 (claimed)
Amazon Textractdocument parserOCR and form/table extraction with per-page pricing inside AWS. Typical: document intake, claims processing.not checkedSOC 2 (claimed)HIPAA-eligible (claimed)ISO 27001 (claimed)
Diffbotweb/knowledge extractionStructured extraction and knowledge-graph construction from web sources. Typical: market monitoring, entity resolution.not checkedvendor-stated security posture
Firecrawlweb/knowledge extractionCrawling and clean markdown extraction for grounding on public sources. Typical: regulatory monitoring, public-source grounding.not checkedvendor-stated security posture
Voyage AIembeddingsDomain-tuned embedding models including legal and finance variants. Typical: retrieval quality, domain RAG.not checkedvendor-stated security posture
NomicembeddingsOpen embedding models with local inference and dataset visualisation. Typical: on-prem retrieval, dataset inspection.self-hostable
Pineconevector databaseManaged serverless vector search with namespace isolation. Typical: tenant-isolated RAG, semantic search.not checkedSOC 2 (claimed)ISO 27001 (claimed)HIPAA-eligible (claimed)
Weaviatevector databaseVector database available managed or self-hosted with hybrid search. Typical: hybrid retrieval, self-hosted RAG.open sourceSOC 2 (claimed)
Qdrantvector databaseOpen-source vector store with payload filtering and on-prem deployment. Typical: air-gapped RAG, filtered retrieval.open sourceGDPR-positioned
Milvusvector databaseOpen-source vector database for very large collections. Typical: large-scale retrieval.open source
pgvectorvector databasePostgres extension keeping vectors under the same RBAC, backup and retention regime as records. Typical: record-bound retrieval, small-scale RAG.self-hostablerecord-retention alignment (claimed)
Letta (MemGPT)agent memory storePersistent agent memory with explicit memory blocks and editing. Typical: long-running agents, personalisation.self-hostable
Mem0agent memory storeMemory layer extracting durable facts from agent conversations. Typical: personalised agents, support copilots.not checkedvendor-stated security posture
Zepagent memory storeTemporal knowledge-graph memory with fact validity intervals. Typical: auditable memory, long-running agents.not checkedGDPR-positionedbitemporal record positioning
Cogneeagent memory storeOpen-source memory/knowledge pipeline building graphs from agent interactions. Typical: knowledge accumulation, research agents.self-hostable

Community-maintained, disputable examples — not an endorsement and not a ranking. Alignments are as claimed by vendors or the source compilation, not verified by RAIN; a certification is shown as a certification only where a certificate or registry reference is recorded.

Disclosure: RAI·N·avigator operates in this category too, so we have a commercial interest in any comparison here. That is why this layer maps product classes to control objectives and lists named products as community-maintained examples — we publish no rankings, no quadrants and no coverage assertions about any vendor, including ourselves.

Select on
Parsing fidelity on your worst document class; retrieval precision/recall on a labelled set; tenant and ACL isolation model; per-vector encryption and erasure path; memory TTL and record semantics; self-host option.
Why this confidence
  • 1 in-scope component of this use case is supplied by this layer (Document Intelligence Engine) — a direct supplied_by path in the graph.
  • The catalog use-case match is strong, so the component set this layer was derived from is reliable.
  • High-risk tier: this layer carries mandatory Chapter III duties, so some tooling in it is non-optional.
  • 16 community-maintained example vendors recorded on the layer node.
  • Selection metrics for this layer are documented, so the shortlist can be compared objectively.
  • Only 1 of 8 components this layer supplies are in your scope — evaluate a narrow subset of its capabilities.
Alternatives
  • Public Transparency Registers & System Cards — confidence strong (70/100, +4 vs. this layer); also covers: AI Register & Model Registry / Factsheets
  • Cryptographic Evidence & Audit Ledger — confidence moderate (68/100, +2 vs. this layer); also covers: WORM / Immutable Audit Vault

Agent Observability & Model Risk Management — covers 1 of your components

Covers: AI Register & Model Registry / Factsheets. This layer supplies 10 components in the graph.
Confidence: moderate (65/100)
Community-maintained examples
LangSmith · Langfuse · Arize AI / Phoenix · Helicone · MLflow · Ragas · Deepchecks · Fairlearn · Fiddler AI · ValidMind · WhyLabs · Evidently AI · Galileo AI · Patronus AI · Arthur AI
Filters to self-hostable, customer-VPC and open-source options when personal or confidential data cannot leave the EU.
ExampleSub-categoryWhat it doesHostingClaimed alignments
LangSmithagent tracing & evaluationTrace capture and evaluation over LangChain/LangGraph runs with dataset-based scoring. Typical: step tracing, regression evaluation.not checkedSOC 2 (claimed)supports Art. 12 record-keeping (claimed)
Langfuseagent tracing & evaluationOpen-source tracing, prompt management and evaluation; self-hostable for retention control. Typical: self-hosted tracing, cost/latency analytics.open sourceGDPR-positionedsupports Art. 12 record-keeping (claimed)
Arize AI / PhoenixML & LLM observabilityProduction monitoring with drift and performance analysis; Phoenix is the open-source tracing side. Typical: drift monitoring, production analytics.not checkedSOC 2 (claimed)drift-monitoring positioning (SR 11-7 style, claimed)
HeliconeLLM gateway & loggingProxy-level logging of prompts, costs and latency across providers. Typical: gateway logging, cost control.not checkedSOC 2 (claimed)supports Art. 12 record-keeping (claimed)
MLflowexperiment & model registryOpen-source tracking, model registry and lineage across training and deployment. Typical: model registry, validation records.open sourcemodel-validation positioning (SR 11-7 style, claimed)
RagasRAG evaluationOpen evaluation metrics for retrieval faithfulness and answer grounding. Typical: grounding checks, RAG regression.not checkedOSS, no vendor certification
Deepchecksvalidation & testingContinuous validation suites for data and model behaviour. Typical: release gating, data validation.not checkedevaluation-evidence positioning
Fairlearnfairness toolkitOpen-source fairness assessment and mitigation for classification and regression. Typical: bias testing, fairness reporting.not checkedOSS, no vendor certificationsupports Art. 10 bias examination (claimed)
Fiddler AImodel performance managementExplainability and monitoring platform aimed at regulated model risk teams. Typical: explainability, model monitoring.not checkedSOC 2 (claimed)model-risk positioning (SR 11-7 style, claimed)
ValidMindmodel risk managementModel validation documentation and workflow for banking model-risk functions. Typical: validation reports, MRM workflow.not checkedSOC 2 (claimed)model-risk positioning (SR 11-7 style, claimed)
WhyLabsdata & model monitoringTelemetry and drift monitoring over model inputs and outputs. Typical: drift detection, data quality monitoring.SaaS (vendor cloud)supports Art. 72 post-market monitoring (claimed)
Evidently AIevaluation & monitoringOpen-source evaluation and monitoring reports for ML and LLM pipelines. Typical: evaluation reports, drift detection.open sourcesupports Art. 72 post-market monitoring (claimed)
Galileo AILLM evaluation & observabilityEvaluation metrics and traces for generative applications. Typical: LLM evaluation, trace inspection.SaaS (vendor cloud)supports Art. 15 accuracy measures (claimed)
Patronus AI · eingestellt (2026-08-31)automated LLM evaluationAutomated scoring and adversarial test suites for generative output. Typical: automated evaluation, red teaming.SaaS (vendor cloud)supports Art. 15 robustness measures (claimed)
Arthur AImodel performance monitoringPerformance, bias and drift monitoring across deployed models. Typical: bias monitoring, performance monitoring.SaaS (vendor cloud)supports Art. 72 post-market monitoring (claimed)supports Art. 10 bias examination (claimed)

Community-maintained, disputable examples — not an endorsement and not a ranking. Alignments are as claimed by vendors or the source compilation, not verified by RAIN; a certification is shown as a certification only where a certificate or registry reference is recorded.

Disclosure: RAI·N·avigator operates in this category too, so we have a commercial interest in any comparison here. That is why this layer maps product classes to control objectives and lists named products as community-maintained examples — we publish no rankings, no quadrants and no coverage assertions about any vendor, including ourselves.

Select on
Trace completeness per agent step; log retention and immutability options; drift/quality metrics available out of the box; evaluation dataset support; export into your audit vault; self-host option.
Why this confidence
  • 1 in-scope component of this use case is supplied by this layer (AI Register & Model Registry / Factsheets) — a direct supplied_by path in the graph.
  • The catalog use-case match is strong, so the component set this layer was derived from is reliable.
  • High-risk tier: this layer carries mandatory Chapter III duties, so some tooling in it is non-optional.
  • 15 community-maintained example vendors recorded on the layer node.
  • Selection metrics for this layer are documented, so the shortlist can be compared objectively.
  • Only 1 of 10 components this layer supplies are in your scope — evaluate a narrow subset of its capabilities.
Alternatives
  • Public Transparency Registers & System Cards — confidence strong (70/100, +5 vs. this layer); overlapping coverage, no additional selected component
  • Cryptographic Evidence & Audit Ledger — confidence moderate (68/100, +3 vs. this layer); also covers: WORM / Immutable Audit Vault

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