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Credo AI is an enterprise AI governance platform that enables organizations to discover, assess, and govern every AI agent, model, and application — continuously and in context. The platform is purpose-built for enterprises that need to move from manual, fragmented governance processes to a comprehensive, automated approach that scales with AI adoption.
The platform consists of four integrated capabilities: AI Registry for discovering and cataloging all AI systems including shadow AI; Risk Intelligence for continuous, contextual risk assessment covering bias, security, privacy, and compliance; Policy Engine for enforcing governance policies through automated workflows and pre-built policy packs; and GAIA (Govern AI Assistant), which provides multi-layer governance across model, agent, application, and network levels.
Credo AI delivers pre-built policy packs for all major regulatory frameworks including the EU AI Act, NIST AI RMF, ISO 42001, SOC 2, GDPR, and HITRUST. These packs include automated evidence generation and audit-ready documentation. The platform integrates natively with enterprise tools including Snowflake, Databricks, AWS, Azure, ServiceNow, Jira, Confluence, Slack, GitHub, and MLflow.
Customers report achieving EU AI Act compliance 10 times faster than manual processes, and the platform has received 12 perfect scores in the Forrester Wave evaluation. Credo AI is available on the Microsoft Marketplace and serves regulated industries including financial services, healthcare, and defense.
- Discovering and cataloging all AI agents, models, and applications across the enterprise with shadow AI detection
- Assessing vendor AI risk through automated vendor portal compliance workflows and third-party risk profiling
- Tracking AI adoption and maintaining a centralized AI registry aligned to internal governance frameworks
- Achieving and demonstrating compliance with the EU AI Act using pre-built automated policy packs
- Implementing NIST AI RMF, ISO 42001, and SOC 2 governance frameworks with automated evidence generation
- Monitoring generative AI applications for hallucination, bias, drift, and emergent agent behavior in real time
- Enforcing custom AI guardrails and governance policies across model and agent deployments at enterprise scale
- Conducting automated red-teaming and continuous risk assessment for AI systems in production environments
- Generating audit-ready artifacts and documentation to support regulatory audits and internal compliance reviews
- Governing multi-agent AI networks by overseeing autonomous agent behavior across application and network levels
- Aligning AI development teams and governance stakeholders through integrated workflows with Jira, GitHub, and Slack
- Managing AI risk classification, stakeholder mapping, and auto-discovery for new AI deployments organization-wide
