Vendor list · AI governance & GRC
AI governance and GRC platforms, scored on the published rubric.
Cohort inclusion criteria
- AI governance & policy: framework mapping (NIST AI RMF, EU AI Act, ISO 42001), policy enforcement, and an AI use-case register.
- Model risk & assurance: bias, fairness, explainability, and robustness testing with a documented model-risk methodology.
- Discovery & monitoring: model and shadow-AI inventory, drift and policy monitoring, and runtime guardrails.
- Compliance automation: automated control-evidence collection and audit-ready reporting across connected systems.
This set spans dedicated AI-governance platforms, AI-extended GRC suites, and AI-usage analytics with a governance angle. Each vendor is scored on its actual coverage of every dimension - a dimension a vendor's product category structurally does not address scores zero, not a penalty for missing evidence.
Rubric (7 dimensions)
- Regulatory-framework coverage (20%) - maintained mapping across NIST AI RMF, EU AI Act, ISO 42001, and SOC 2 with control libraries and crosswalks. The heaviest-weighted dimension.
- Model + shadow-AI discovery (15%) - automated discovery of models, AI apps, agents, and shadow-AI usage, with a maintained inventory.
- Model-risk, bias + explainability depth (18%) - quantitative bias, fairness, explainability, and robustness testing.
- Continuous monitoring + runtime guardrails (15%) - production drift and policy monitoring versus a one-time audit.
- Evidence + audit automation (14%) - automated control-evidence collection and audit-ready reporting.
- Integration breadth (AI/data stack) (10%) - connectors across MLOps, cloud, model registries, and the data stack.
- Regulatory currency (8%) - speed of tracking new regulations and standards into the product.
Platforms in scope
Each platform below is scored against the rubric above. The score is the weighted total across the seven dimensions, after integration, scale, and pricing-transparency penalties.
01 Credo AI Purpose-built enterprise AI governance platform: framework mapping, model risk, and runtime guardrails Cross-industry 95 /100
Top strength Cohort-leading breadth: pre-built policy packs for EU AI Act, NIST AI RMF, ISO 42001 and SOC 2, automated model and shadow-AI discovery, quantitative risk testing with red-teaming, continuous trace evaluation, and automated audit-ready evidence - validated by Forrester Wave...
Top gap No public pricing (demo-only; pricing page returns 404) and no exact funding/headcount/HQ disclosed on the public surface; contact email not exposed.
Best for Enterprise teams (Fortune 500, regulated industries) needing mapped controls for EU AI Act, NIST AI RMF and ISO 42001 together with production monitoring and audit automation.
02 OneTrust Privacy/GRC incumbent extending into AI governance: AI inventory, framework-aligned risk tiering, runtime monitoring and audit-evidence... Cross-industry 76 /100
Top strength Broad maintained compliance-framework library (EU AI Act, NIST, ISO 42001 plus 25+ data/security regs) backed by a dedicated regulatory-intelligence function (40+ in-house researchers, 500+ lawyers, 300 jurisdictions); recognized by Gartner as an AI Governance Platform (2025...
Top gap No public evidence of quantitative bias/fairness or explainability/red-team testing depth; pricing is quote-only across all packages; automated shadow-AI discovery breadth un-evidenced on the public surface.
Best for Enterprise teams already using OneTrust privacy or GRC modules that need to extend existing controls to AI inventory, EU AI Act mapping, and runtime oversight.
03 ModelOp Enterprise AI lifecycle management and governance platform (AI system of record) Cross-industry 75 /100
Top strength Cohort-leading model-risk testing (bias/drift/performance), real-time runtime monitoring, and 50+ MLOps/cloud/data/GRC integrations as a neutral enterprise AI control tower.
Top gap No automated shadow-AI discovery (inventory is intake/registration-based); pricing is quote-only with no public tier; SOC 2/ISO certification status not on the public surface.
Best for Large regulated enterprises (banks, F500) needing continuous model-risk monitoring, automated audit-evidence collection, and integration with existing MLOps and GRC stacks.
04 Scrut Automation Security-first GRC platform with continuous control monitoring and automated audit evidence, extending into AI governance via ISO 42001 and... Cross-industry 51 /100
Top strength Automated control-evidence collection and 24/7 continuous control monitoring across 60+ frameworks, the cohort calibration anchor for evidence/audit automation.
Top gap No model inventory/shadow-AI discovery and no quantitative model-risk (bias/explainability) testing; AI governance is via ISO 42001 + NIST AI RMF mapping, not model-level testing.
Best for Security-first startup-to-enterprise teams needing automated GRC evidence workflows plus ISO 42001/NIST AI RMF coverage, without dedicated model-risk tooling.
05 Oximy AI adoption and shadow-AI discovery engine for the enterprise Cross-industry 48 /100
Top strength Automated network-layer discovery of 6,500+ AI tools and shadow-AI usage with no browser extensions or API keys, plus a continuous detect-intervene-measure loop and broad identity/network/HRIS connectors.
Top gap No model-risk, bias or explainability testing and no maintained framework control library or crosswalks; framework coverage is alignment-claim only.
Best for Enterprises that need automated discovery of shadow AI, usage analytics and employee-behavior policy enforcement, without requiring model-registry or MLOps integrations.
06 AlignAI AI Operating Model platform for refining, approving and orchestrating enterprise AI initiatives across the governance lifecycle Cross-industry 39 /100
Top strength Connective intake-to-impact governance layer: use-case manager, playbook studio and approval routing that sits on top of an existing stack (SharePoint, ServiceNow, Jira, Power BI) with bidirectional sync, a documented REST/OAuth 2.0 API and SOC 2 Type II certification.
Top gap Process-governance tool, not a model-testing one: no quantitative bias/explainability/red-team testing; framework coverage is a single ISO 27001 reference with no maintained crosswalk library; several flagship GRC/MLOps connectors (Archer, Databricks, OneTrust) are roadmap;...
Best for Mid-to-large enterprises and AI COEs standardizing intake, prioritization and approval of AI initiatives on a Microsoft/Jira stack.
Missing a platform we should evaluate? Submit it here. We add platforms that meet the inclusion criteria above and score them on the published rubric. Vendors that submit are not given preferential treatment - methodology is published in plain sight.