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CognitiveView vs trail

trail

6.4#24 in ai governance tools
WebAPISelf-hosted
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What both publish

FactCognitiveViewtrail
AI inventoryIts features include inventorying internal and third-party AI tools, including shadow AI.The platform maintains a centralized registry of AI use cases, systems, agents, and models.
HeadquartersLinkedIn lists headquarters at 200 E 6th St, Suite 230, Austin, Texas 78701, United States.Munich, Germany
IntegrationsListed integrations include AWS, Microsoft Azure, Google Cloud, Databricks, DeepEval, Evidently, AI Fairness 360, Salesforce, ServiceNow, Microsoft and OpenTelemetry.The site lists OneTrust, Collibra, ServiceNow, SAP LeanIX, Confluence, Jira, GitHub, GitLab, SharePoint, Notion, Databricks, MLflow, Hugging Face, ZenML, and n8n among its integrations.
Intended usersThe pricing page describes Starter as suited to startups, early AI teams, and first enterprise pilots; Growth targets companies with AI in production and regulated or high-impact use cases.The product is designed for organizations building or using AI, with regulated enterprises, risk and compliance teams, and AI teams identified as likely users.
ProductCognitiveView describes itself as an AI governance platform for AI risk, compliance, and responsible AI management.Trail provides AI governance and GRC tools that automate compliance work for AI systems and software.
Risk managementRisk management includes a risk taxonomy, heatmaps, portfolio views and customizable categories and scoring.Trail includes a curated library of over 170 AI risks, including risks from MIT, NIST, OWASP, and BSI.

CognitiveView plans

  • FreeFree
  • Standard$8 a year
  • Plus$14 a year
  • AI Governance Starter Pack$149, paid once
  • AI Agent Assurance$10,000, paid once
  • Specialized AI Assurance$10,000, paid once

trail plans

No prices published.

Pick CognitiveView if…

CognitiveView suits teams that need to inventory AI tools, assess risk, map systems to governance frameworks, and manage approvals or compliance evidence. Its Starter offering is described for startups, early AI teams, and first enterprise pilots, while Growth targets companies with AI in production and regulated or high-impact use cases.

Pick trail if…

You want what its maker publishes above — check its page for the details.

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