Virtue AI

Virtue AI offers a comprehensive platform for AI security and compliance, enabling enterprises to develop and deploy artificial intelligence systems responsibly. The company was co-founded by a team of distinguished AI and security researchers: Bo Li (CEO), Dawn Song (Board Director), Carlos Guestrin (Chief Scientist), and Sanmi Koyejo (Chief Responsible AI Officer). This founding team brings over 80 years of collective experience in AI safety and security research from institutions like UC Berkeley, Stanford, and UIUC.

The company's platform addresses critical risks unique to AI, such as hallucinations, prompt injections, data poisoning, and model leakage, which traditional cybersecurity measures often fail to cover. Virtue AI provides an integrated suite of products to manage these risks throughout the AI lifecycle. Key offerings include VirtueRed, an algorithmic red-teaming platform that assesses over 320 risk categories; VirtueGuard, which provides real-time, multimodal guardrails for text, image, audio, video, and code across more than 90 languages; and VirtueAgent, for securing autonomous AI agents. These guardrail models are noted for operating at speeds significantly faster than alternatives while delivering superior performance.

Virtue AI operates on a B2B model, targeting enterprise clients in sectors where AI security is critical, such as financial services, healthcare, and insurance. The company has secured prominent clients like Uber and Glean. In April 2025, Virtue AI announced it had raised $30 million in a combined Seed and Series A funding round co-led by Lightspeed Venture Partners and Walden Catalyst Ventures, with participation from other investors. This capital is intended to expand its platform capabilities, increase its market presence, and recruit talent.

Keywords: AI security, AI compliance, generative AI safety, AI risk management, enterprise AI, large language models, red teaming, AI guardrails, model security, prompt injection, data poisoning, hallucination detection, autonomous systems security, AI governance, adversarial machine learning, AI safety research, regulatory compliance, multimodal AI security, responsible AI, AI lifecycle management