Willow Admin Console

A managed access and enablement control plane for the whole organization. It provides employee self-service, machine users, fine-grained per-agent and per-action policy, and IT-run identity and lifecycle. It is proven at Wix across roughly 5,000 weekly active users.

Runlayer Control Plane

An AI control plane centered on runtime security and a large MCP catalog. It offers threat detection through Guard, agent identity and policy, and an on-demand agent builder, all aimed at the platform and security team.

Willow vs Runlayer, side by side

Who Each Solution Is Best For

Who Willow is built for

Organizations bringing AI to every team without a security-review backlog. It fits when you need:

• Employee self-service so adoption does not bottleneck on IT
• Machine users for automation
• Fine-grained policy that IT and security can run and adapt themselves
• Shadow-AI visibility before the first incident, including vibe-coded apps like Lovable and Base44 before they connect to internal systems
• Deployment anywhere your security team requires, including air-gapped and EU

Who Runlayer is built for

Platform and security teams that want an AI control plane centered on runtime threat detection, the largest possible catalog of MCP servers, and an on-demand agent builder. It fits when:

• Runtime threat detection at the MCP layer is the primary job
• You want the largest possible catalog of MCP servers
• You want an on-demand agent builder on the platform
• The work is securing and scaling agent-to-tool traffic for a technical team

Governed Background Agents

Autonomous agents with their own identity, scoped to least privilege, and governed like every other call.

Willow approach

• Every background agent has its own identity and access key, so it authenticates as itself and its capabilities define its blast radius.
• Scope each agent to the exact tools, skills, and rules it needs, and nothing more.
• Run agents on any platform, including Custom, Claude Managed Agents, and AWS AgentCore.
• Every call passes through the gateway under the same guards, policy, and logging as any other traffic.
• A risk-scored inventory answers which agents can touch a given system, and webhook triggers start an agent when something happens in a connected app.

Runlayer approach

• Runlayer Agents is an agent builder for creating agents on demand, with Slack integration and self-healing agents.
• Its agent identities, called Agent Accounts, are currently in beta.

Bottom Line

Both let you run agents, but they optimize for different things. Runlayer optimizes for building agents quickly. Willow optimizes for governing autonomous agents, giving each one its own scoped identity, least-privilege access, and full audit, so security can say yes to unattended work.

Infrastructure as Code

Manage your whole AI configuration the way engineering manages everything else, as code in Git.

Willow approach

• Sync your toolkits, skills, commands, MCP servers, and clients to a GitHub repository as version-controlled files.
• Review every change through pull requests, and keep a full history of who changed what.
• Two-way sync keeps Willow and the repository in step, so a change in either place flows to the other.
• Authentication secrets are never written to the repository, so the configuration is safe to store.

Runlayer approach

• Runlayer connects to your identity provider and tools and manages configuration in its own control plane.
• It does not market a Git-based, pull-request workflow for its full configuration.

Bottom Line

This is where engineering teams lean in. Willow lets platform teams manage AI governance the same way they manage the rest of their stack, in Git with review and history, rather than by clicking through a console.

Self-Service and IT Approval Workflows

Employees self-serve the tools they need, and IT approves once instead of drowning in tickets.

Willow approach

• Employees browse approved tools in the Connect Panel and marketplace and connect any AI client in one click, with no IT ticket.
• IT approves the catalog once, and sets a per-user policy of none, needs-approval, or allow for user-added MCPs.
• A require-approval guard holds a specific tool call pending a decision, with an approval page that shows what fired and why.
• When your identity provider deprovisions a user through SCIM, Willow removes that user, and because access flows through their groups, their access to the MCPs and tools they had goes with it.

Runlayer approach

Runlayer publishes a governed path into the AI clients teams already use, and admins approve or block through Watch and policy.

Bottom Line

Both keep IT in control. Willow is built so adoption never bottlenecks on IT, because employees self-serve, IT approves the catalog once, and lifecycle changes close themselves.

Guards and DLP

A configurable content layer that redacts, blocks, warns, or requires approval on prompts and actions.

Willow approach

• Guards inspect every tool call and response at runtime, and inspect content before it is published at build-time.
• Built-in detectors cover secrets and PII, and you can add regex, JSONata, LLM, or custom function checks.
• When a guard fires it can redact the sensitive part, warn, require approval, or block, and the most restrictive outcome wins.
• Build-time guards stop non-compliant content before it ever reaches a user's AI client.

Runlayer approach

Runlayer Guard focuses on runtime threat detection, with models tuned for MCP attack vectors and intent-drift detection.

Bottom Line

These solve different halves of the problem. Runlayer leads on runtime threat detection, and Willow's guards are the DLP and policy-as-code layer, configurable to redact, require approval, or block on both prompts and actions, at build-time and runtime.

ROI and Cost Optimization

See where tokens go and cut them, not just report the spend.

Willow approach

• Token Usage Analytics shows where tokens come from across MCP servers, toolkits, skills, and tool responses, by team, tool, and use case.
• Reduce cost by tightening toolkits, moving long skill content into references, and optimizing the tool-response output format, including JSON Compact, CSV, YAML, or TOON.
• The result is fewer tokens per call, not only a report of what was spent.

Runlayer approach

Runlayer's ROI and Observability reports usage, spend, and adoption across users, clients, tools, and agents.

Bottom Line

Both give visibility. Willow goes a step further and actively reduces the tokens each call consumes, so cost control is built into how the platform runs, alongside analytics by team and tool.

Why enterprises pick Willow

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

Wix needed a secure, governed way to connect employees and agents to internal tools, documentation, and workflows. With Willow, the AI Core team built the enterprise MCP infrastructure that now supports nearly 600 tools and 2M+ weekly tool calls across engineering, product, design, HR, finance, legal, and business teams.

FAQs

Everything you need to know about Willow compared to Runlayer

What is the difference between Willow and Runlayer?

Willow is an organization-wide AI access and enablement platform, with employee self-service, a curated catalog, machine users, endpoint shadow-AI discovery, and deployment anywhere including air-gapped and EU. Runlayer is an AI control plane centered on runtime threat detection and the largest MCP catalog, aimed at the platform and security team. Willow fits organizations rolling AI out across many teams with governance they can run themselves.

Is Runlayer a Willow alternative?

Both are AI control planes, but they are built around different priorities. Runlayer centers on runtime security and catalog scale. Willow centers on organization-wide governance, employee enablement, and deployment breadth.

Which is better for enterprise AI governance, Willow or Runlayer?

It depends on the job. If you are governing AI adoption across the whole organization with fine-grained policy your own IT and security run, self-service for every team, and deployment anywhere, Willow is the better fit. If your priority is MCP-layer runtime threat detection and the largest raw catalog, Runlayer is strong there.

How is Runlayer priced, and is it open source?

Runlayer is a commercial, managed platform and is not open source. Willow is also commercial and managed, and it adds deployment anywhere, including on-premises and air-gapped, for organizations that need it.

Does Willow detect shadow AI?

Yes. Willow's endpoint scan agent discovers unmanaged MCPs, skills, and AI agents across web and local usage, with risk scoring, and a browser extension adds visibility into web AI usage. This extends to vibe app monitoring, tracking employee use of vibe-coding app builders like Lovable and Base44 and flagging when those apps are hooked into internal systems. Runlayer also offers shadow-AI discovery through Watch, so both cover shadow AI, and the difference is scope and how it is run.

How is Willow deployed?

Willow deploys as SaaS, dedicated cloud, on-premises on AWS, GCP, or Azure, hybrid, and air-gapped, with EU residency, and it typically goes live in about ten days. Runlayer deploys in the cloud, self-hosted, or single-tenant through VPC, Terraform, and Helm.

Can I migrate from Runlayer to Willow?

Yes. You can bring your configuration over by adding your MCP servers from the catalog, as custom servers, or through the API, importing your skills from a GitHub repository, and importing your users, so Willow can run alongside your existing tools while you transition.