Credo AI
The trusted enterprise AI governance platform for measuring, managing, and governing AI risk across every agent, model, application, and vendor.
- Pricing:
- Free
Overview
Credo AI is an enterprise AI governance platform founded in 2020 to help organizations manage AI systems responsibly, ensuring compliance, risk management, and ethical AI practices across the entire AI lifecycle. Built from the ground up for governance—not bolted onto a generic GRC tool—the platform provides a continuous governance loop that assesses, governs, and monitors AI systems in production. As the creator of the AI governance category, Credo AI is recognized as a Leader in the Forrester Wave™ for AI Governance Solutions (Q3 2025) and has been named among Fast Company's Most Innovative Companies in Applied AI.
The platform is powered by a Governance Knowledge Graph that fuses global regulatory intelligence with business context from 300+ integrations and forward-deployed governance experts. Core capabilities include AI Registry for discovering and cataloging every AI system, agent, vendor, and model; Shadow AI detection for full visibility into unsanctioned AI usage; Dynamic Risk Scoring driven by continuous monitoring and drift detection; and a Policy Engine that translates policy and regulatory requirements into executable code. Pre-built policy packs cover major frameworks such as the EU AI Act, NIST AI RMF, ISO 42001, OMB M-25, CO ADMT, and NAIC. The platform also includes GAIA (Govern AI Assistant), an AI-powered assistant that compresses weeks of governance work into hours by automating intake, registration, risk mapping, and control mapping.
Credo AI is uniquely positioned for the agentic era, treating agents as first-class governed entities with an Agent Registry, Agent Governor, and a purpose-built agentic risk and control library addressing tool misuse, scope drift, and inter-agent risk. Native integrations with Snowflake, Databricks, AWS, Azure, ServiceNow, Jira, Confluence, Slack, GitHub, and MLflow allow enterprises to embed governance directly into existing AI and data pipelines without major infrastructure changes. This makes it possible to govern systems that act autonomously in milliseconds—something impossible with manual, spreadsheet-based, or point-in-time governance methods.
Trusted by leading enterprises across insurance, financial services, federal, and healthcare, Credo AI enables measurable trust for every AI system. Organizations use the platform to build generative AI guardrails, assess vendor risk, track AI adoption, comply with evolving regulations, scale AI governance and risk management, and become audit-ready. With advisory services, industry benchmarking, and continuous regulatory intelligence, Credo AI helps enterprises move AI from pilot to production with confidence, transparency, and accountability.
Core capabilities
- AI Registry
- Discover and catalog every AI system, agent, model, and vendor, with full visibility into shadow AI and risk classification.
- Agent Governance
- Registry and governor for AI agents, treating agents as first-class governed entities with agent cards and purpose-built controls.
- Policy Engine
- Turn policy into code with pre-built policy packs, compliance mapping, automated workflows, and audit-ready evidence recording.
- Risk & Compliance Management
- Continuous contextual risk assessment with dynamic risk scoring, drift detection, real-time alerts, and a comprehensive risk/control library.
- Regulatory & Policy Intelligence
- Ready-to-deploy policy packs for EU AI Act, NIST AI RMF, ISO 42001, OMB M-25, CO ADMT, and NAIC, maintained by industry experts.
- Govern AI Assistant (GAIA)
- AI-powered intake and registration, risk & control mapping, and automated governance workflows that compress weeks of work into hours.
- Audit Trails & Reporting
- End-to-end evidence recording, audit-ready reports, and transparent documentation for internal and external audits.
- Native Integrations
- Integrates directly with Snowflake, Databricks, AWS, Azure, ServiceNow, Jira, Confluence, Slack, GitHub, and MLflow for seamless governance in existing stacks.
Use cases
- Building Generative AI Guardrails
- Assessing Vendor Risk Across AI Suppliers
- Tracking AI Adoption and Shadow AI Discovery
- Complying with Regulations such as the EU AI Act and NIST AI RMF
- Scaling AI Governance and Risk Management from Pilot to Production
- Becoming Audit-Ready with Continuous Evidence Recording
- Governing Autonomous AI Agents in the Agentic Era
Who it's for
AI Governance Leaders and Chief AI Officers, Chief Data Officers and Data Science Executives, Risk, Compliance, and Audit Teams, AI/ML Engineers and Developers, Enterprise Architects and Platform Teams, Federal and Public Sector Agencies, Insurance, Financial Services, and Healthcare Organizations
