Enterprise AI inventory explained: learn why it matters for compliance and risk, and how Holistic AI automatically discovers, ...

As enterprise AI systems evolve from hand coded applications and static AI models to autonomous agents, governance is also entering a new phase. Traditional AI governance approaches enforced in ...

Join the organizations that turned governance from a blocker into an enabler. Full visibility, continuous risk testing, and compliance proof — on autopilot.

Worth $23.196 billion USD in 2021, China’s Artificial Intelligence (AI) market is expected to triple to $61.855 billion by 2025 and the Chinese government expects for AI to create $154.638 billion USD ...

Policymakers around the world are increasingly recognizing the importance of regulation and legislation to promote safety, fairness, and ethics in the use of AI tools. In this blog post, we’ll look at ...

Traditional AI governance relies on documentation, reviews, and after the fact audits. You write a policy, assess a model, file a report, and hope everything holds once the system goes live. Agentic ...

You can identify every AI system in your organization. You can assess each one for risk. But if the policies you write stay as documents that nobody enforces consistently, governance breaks down the ...

An agent graph is an interactive knowledge graph on our Holistic AI Governance platform that converts raw execution logs from your AI agents into a structured visual map of everything that happened ...

An efficient, independent audit of your due diligence obligations and compliance with signed Codes of Conduct or crises protocols. Identify your high-risk AI use cases. Adopt appropriate and targeted ...

Our industry-leading AI governance platform delivers continuous oversight across the full AI lifecycle, enabling confident innovation at scale.

"Holistic AI's Governance Platform enabled us to systematically govern AI use cases across Unilever's value chain – from manufacturing to supply chain optimization – ensuring compliance, mitigating ...

Bias in artificial intelligence systems is a critical issue that affects fairness and trust in these technologies. It can manifest in various forms, such as gender, race, age, and socio-economic ...