Willow Raises $7M to Address One of Enterprise AI’s Biggest Blind Spots: Agent Governance

As enterprises increasingly deploy AI agents to handle tasks such as software development, workflow automation, customer support, and internal operations, many are discovering that existing security and identity systems were not designed to manage autonomous software acting on behalf of employees. AI agents often require access to sensitive applications, databases, and business systems, creating new governance challenges around permissions, monitoring, and accountability.

To address this emerging issue, Willow has raised $7 million in seed funding led by Hetz Ventures, with early backing from Wix co-founder and CEO Avishai Abrahami and Wix President Nir Zohar. The company is developing an identity and access management platform specifically for AI agents, giving enterprises visibility into how agents interact with internal systems, what data they can access, and what actions they are authorized to perform.

AI Agents Are Moving Faster Than Enterprise Controls

The rapid adoption of AI agents has created a new operational reality for enterprises. Organizations are increasingly deploying agents to assist with coding, research, workflow automation, customer support, and countless other tasks. Many of these agents operate autonomously, interacting with internal systems and business-critical data.

While this shift promises significant productivity gains, it alo introduces new risks. AI agents can be granted broad access to enterprise resources, often without the visibility, auditability, and governance frameworks that organizations have spent decades building for human employees. According to Willow, many companies are already experiencing incidents tied to agent behavior, highlighting the growing need for oversight.

This emerging challenge has given rise to an entirely new category of enterprise software focused on AI governance, identity, and access management for autonomous systems.

Building an Identity Layer for AI Agents

Founded by former Wix engineers Eyal Ben Ezra, Shalev Shalit, and Idan Chetrit, Willow describes itself as an identity and access platform designed specifically for AI agents. Rather than replacing existing AI models or agent frameworks, the platform sits between AI agents and enterprise systems, providing organizations with centralized control over how agents interact with company resources.

The company’s platform allows enterprises to connect AI agents—including systems built on Claude, ChatGPT, Gemini, Codex, Cursor, n8n, and custom frameworks—to internal applications while applying governance policies, runtime permissions, audit trails, and security controls. Willow positions itself as a universal governance layer that works across multiple AI ecosystems rather than being tied to a single model provider.

A key differentiator is its focus on runtime governance. Instead of granting broad, permanent permissions, Willow generates access dynamically based on the specific task an agent is performing. The platform also provides centralized visibility into agent activity, helping organizations discover unauthorized AI usage and manage what is often referred to as “shadow AI.”

From Internal Wix Deployment to Commercial Platform

One factor that likely strengthened investor confidence was Willow’s ability to validate its technology inside a large enterprise before emerging from stealth.

The company says its platform has already been deployed across Wix, supporting more than 5,000 employees. According to Willow, the infrastructure now supports hundreds of internal tools and processes a substantial volume of weekly AI-driven interactions across departments including engineering, product, finance, legal, and human resources.

That experience provided Willow with a real-world testing environment for understanding how enterprises actually deploy AI agents at scale—a challenge many organizations are only beginning to face.

A Marketplace Approach to Enterprise AI Connectivity

Beyond governance, Willow is building an ecosystem designed to simplify enterprise AI adoption.

The platform includes a marketplace of pre-built integrations, connectors, skills, and plugins that allow organizations to connect AI agents to business systems without creating custom integrations from scratch. According to the company, enterprises can deploy these capabilities while maintaining centralized authorization, compliance, and audit requirements.

This approach reflects a broader trend in enterprise AI, where organizations increasingly need infrastructure that enables agents to interact with business applications while preserving security and compliance requirements. As companies adopt multiple AI models and agent frameworks simultaneously, centralized governance layers may become as important as the underlying models themselves.

Why AI Agent Governance Could Become a Critical Enterprise Category

The rise of AI agents is creating a challenge unlike previous software waves. Traditional security tools were designed to govern human users, applications, and infrastructure. Autonomous AI systems introduce a new layer of decision-making that often falls outside existing governance frameworks. Research and industry analysis increasingly point to runtime visibility, auditability, and permission management as critical components of safe enterprise AI adoption.

This is creating an opportunity for companies focused on what could become a foundational layer of enterprise AI infrastructure. As organizations deploy increasing numbers of agents across multiple platforms, they may require centralized systems capable of managing identity, permissions, compliance, and observability across an increasingly complex AI environment.

Willow’s emergence from stealth reflects a growing recognition that enterprise AI adoption is no longer just about building smarter models. It is also about ensuring those models and agents operate within clear organizational boundaries. As AI agents become permanent members of the enterprise workforce, the companies that can provide visibility, control, and accountability may become some of the most important players in the next phase of AI infrastructure.