Zenity Raises $38M Series B to Secure Enterprise AI Agent Deployment
AI Agent News
Zenity secured $38 million in Series B funding led by Third Point Ventures and DTCP, bringing total capital raised to over $55 million as enterprises grapple with a fundamental infrastructure bottleneck: securing AI agents at scale.
The timing reflects a critical enterprise adoption paradox. While Forbes reports over 51% of companies actively use AI for process automation and Microsoft notes daily Copilot usage has nearly doubled quarter-over-quarter, only 11% of CIOs have fully implemented AI according to Salesforce research. The primary constraint isn’t technological capability—it’s security infrastructure.
The Governance Gap
Enterprise AI agent deployment has outpaced security frameworks by orders of magnitude. Zenity’s research reveals the average large enterprise operates approximately 80,000 AI agents, applications, and automations built on low-code platforms, with over 62% containing security vulnerabilities.
This explosion stems from AI democratization: business users across departments now build and deploy agents without traditional IT oversight. The shared responsibility model mirrors early cloud adoption, where security teams lacked visibility into what applications existed, how they accessed data, or what risks they introduced.
Microsoft’s strategic investment through M12 signals recognition that this gap threatens broader enterprise AI adoption. The company’s own research shows enterprise copilots face easy exploitation without proper governance, as Zenity demonstrated at Black Hat 2024 by taking control of Microsoft 365 Copilot systems without compromising user accounts.
Architecture for Agentic Security
Zenity’s platform addresses three fundamental enterprise security challenges that traditional tools cannot handle:
Autonomous Behavior Monitoring: Unlike static applications, AI agents operate with adaptive autonomy that changes behavior based on context and learning. Zenity provides real-time visibility into agent decision-making patterns and identifies when behavior deviates from expected parameters.
Multi-Chain Interaction Security: Agentic AI involves complex autonomous interaction chains—agent-to-agent, agent-to-system, agent-to-human workflows. The platform maps these interaction patterns and identifies potential attack vectors across the entire chain.
Low-Code Supply Chain Governance: Most enterprise AI agents are built on low-code platforms that introduce third-party components and dependencies. Zenity extends its proven low-code security expertise to provide supply chain visibility and vulnerability assessment for AI agent development.
Evidence of Enterprise Adoption
Fortune 500 deployment across financial services, technology, manufacturing, energy, and pharmaceutical industries demonstrates enterprise-scale validation. The company reports over 3x year-over-year growth, indicating strong market pull for governance solutions.
Zenity’s community-driven approach adds credibility: the team led development of the OWASP Top 10 for Low-Code/No-Code Security and recently launched the GenAI Attacks Matrix, establishing industry-standard security frameworks that competitors adopt.
Partnership with Slalom consulting expands reach into enterprises seeking guidance on secure AI agent adoption, while Microsoft’s strategic investment provides validation and integration pathways into existing enterprise security stacks.
Market Infrastructure Shift
This funding represents infrastructure maturation from experimental AI to production-grade enterprise deployment. Security governance is transitioning from post-deployment auditing to pre-deployment risk assessment and continuous monitoring.
The emergence of dedicated AI agent security platforms reflects a broader pattern: as AI capabilities democratize, specialized infrastructure emerges to manage complexity at scale. This mirrors the evolution from monolithic applications to microservices, where new orchestration and monitoring tools became essential.
Third Point Ventures and DTCP’s investment thesis centers on Zenity’s first-mover advantage in a market category that didn’t exist two years ago but now represents a fundamental enterprise infrastructure requirement.
Looking Forward
Enterprise AI agent security will likely evolve toward zero-trust architectures specifically designed for autonomous systems. This includes continuous behavioral validation, cryptographic attestation of agent actions, and formal verification of agent decision processes.
The next 6-12 months will test whether security-first approaches can keep pace with AI agent proliferation. Zenity’s research suggesting 80,000+ agents per enterprise indicates the scale of challenge, while their 62% vulnerability rate suggests the urgency.
Successful enterprises will likely adopt AI agent governance platforms as prerequisite infrastructure, similar to how cloud security posture management became mandatory for AWS/Azure deployments.
AI agent orchestration platforms like Overclock complement security governance by providing structured deployment workflows that integrate with enterprise security policies. Learn more about building secure, auditable AI agent workflows at overclock.work.