Willow vs Airia: Focused Employee AI Governance Without a Larger Agent Platform - At a glance:

Willow lets IT, security, and AI enablement teams find employee AI and distribute approved tools, skills, policies, and agent access.

Airia combines AI discovery, agent development, model routing, cost management, and governance reporting in one platform.

The core difference

Willow keeps employee AI governance focused. Airia adds agent building and model management. Willow gives IT direct coverage across employee devices, browsers, clients, identities, tools, and agents. Airia requires a broader platform rollout when agent building and model management are also in scope.
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Where Willow leads: direct control over employee AI

Willow lets IT and security govern employee AI without requiring them to deploy agent-building and model-routing capabilities.

• See exactly what developers configured. Find supported local MCP settings, AI clients, skills, Cursor rules, CLAUDE.md, and AGENTS.md across managed macOS and Windows devices.
• Manage AI clients directly. Apply policies and guards in supported coding clients and web AI services, alongside gateway controls and device deployment.
• Distribute approved AI tools and skills. Publish governed skills, toolkits, plugins, and tools for employees to use in their preferred supported AI clients.
• Control machine-user and agent access. Assign owners, scoped capabilities, credentials, secret rotation, triggers, and audit attribution to machine users and background agents.

When to choose Airia

Choose Airia only when agent building and model management lead the project, and all of it must come from the same platform.

• Replace or add model management. Airia can choose models by policy, cost, latency, and availability, then compare versions and control rollout and retirement. This matters when your team also owns the model layer.
• Build applications inside Airia. Business and technical teams can assemble agents, workflows, data retrieval, human approvals, APIs, chat, browser, Slack, and Teams interfaces in Airia.

If building agents and owning the model lifecycle is the project, Airia fits. If the priority is finding and governing the AI employees already use, that is where Willow starts.

Proven at enterprise scale

"We are six to ten months ahead of most companies in AI adoption. More code to production, fewer incidents, real outcomes. Willow is what made it possible to move that fast without slowing down our security posture."Asaf Yonay, Head of AI Core, Wix

• ~5,000 weekly active users at Wix
• ~600 governed tools and MCPs
• 2M+ governed tool calls each week

Bottom line

Willow gives IT focused governance across employee devices, browsers, clients, identities, tools, skills, and agents. Airia combines employee controls with agent building, model management, and governance reporting.

Use Willow when employee AI governance is the priority. Choose Airia only when the same purchase must also cover agent building, model lifecycles, and formal governance reporting.

FAQs

What is the main difference between Willow and Airia?

Willow finds and governs employee AI across devices, browsers, clients, identities, tools, skills, bots, and agents. Airia focuses on agent building, model lifecycles, and formal governance reports.

Which product finds AI that employees did not register with IT?

Willow finds supported local AI clients, MCP settings, skill files, and agent instructions on managed macOS and Windows devices. Airia starts from the agents, models, and applications built or managed inside its own platform.

When should I choose Willow?

When you need to find AI that employees adopted without registering it, then govern that use across devices, browsers, clients, tools, skills, bots, and agents.

When should I choose Airia?

Choose Airia only when agent building, model lifecycle management, and formal governance reporting must come from the same platform.