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Alice Raises $140M to Pair Model Testing With Enterprise AI Guardrails

The former ActiveFence is funding a lifecycle security pitch: test models for hostile behavior before launch, then apply customer-specific controls after AI reaches company data and tools.

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Alice Raises $140M to Pair Model Testing With Enterprise AI Guardrails
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Alice has raised 140 million dollars to build one security platform for two moments in an AI system’s life: before a model launches, and after an enterprise connects it to company data and tools. Apax Digital Funds led the round, and will join Alice’s board. The financing brings the company’s reported total funding to 280 million dollars. Alice, formerly known as ActiveFence, is headquartered in New York and Tel Aviv. Its pitch starts with Rabbit Hole, a proprietary archive built over nearly a decade of tracking fraud, extremism, coordinated manipulation, and other hostile activity across the open web. Before release, Alice uses that intelligence to run malicious prompts and agentic tasks against models, looking for jailbreaks, prompt injection, and other erratic behavior. After deployment, its runtime guardrails let an organization enforce its own rules while monitoring inputs and outputs in real time. That distinction matters. Model labs need broad defenses against attacks that generalize across systems, while enterprises need controls tied to their own compliance, data-handling, and behavior requirements. Alice says it has more than 150 researchers, works with eight of the ten leading AI model labs, and protects over three billion people online. The company also reports nearly 100 million dollars in annual recurring revenue and more than 500 percent growth in its AI business over two years. The key question is whether patterns from web abuse can reliably become safeguards that work both before launch and inside highly specific enterprise deployments.

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Alice has secured $140 million from Apax Digital Funds and other investors, bringing reported total funding to $280 million, to scale a security platform spanning model evaluation and enterprise runtime controls. Its approach connects Rabbit Hole, a nearly decade-long archive of online abuse, with pre-release jailbreak and prompt-injection testing and post-deployment policy enforcement. The practical test is whether...

  1. 01

    Apax Digital Funds led the round; Apax will join Alice’s board.

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    Alice was formerly known as ActiveFence and is headquartered in New York and Tel Aviv.

  3. 03

    The company reports nearly $100 million in annual recurring revenue and more than 500% AI-business growth over two years.

Alice has raised $140 million to expand an AI security platform built for two different moments: before a model is released and after an enterprise puts it to work. The company’s bet is that adversarial behavior observed elsewhere online can strengthen both model tests and production safeguards.

Apax Digital Funds led the financing, which Alice says brings its total funding to $280 million. MoreTech, Phoenix Financial, Resolute Ventures, Grove Ventures, CRV, Highland Europe, Vintage Investments, Norwest, NFX, and Claltech participated. Apax Digital will join Alice’s board.

Alice, formerly known as ActiveFence, plans to put the money into its AI platform, the team behind its Rabbit Hole intelligence dataset, and go-to-market expansion for model labs and enterprises. The company is headquartered in New York and Tel Aviv.

Before release, after deployment

For foundation-model developers, Alice offers pre-release stress testing. Researchers simulate malicious prompts and agentic tasks to find unexpected behavior and harden models against jailbreaks and prompt injection, where instructions attempt to override a model’s intended rules.

Once a system is live, the company says customers can set internal policies, run attack simulations, and monitor inputs and outputs in real time. That shifts the task from improving a general-purpose model to enforcing the specific compliance, data-handling, and behavior requirements of the organization using it.

A web-abuse archive becomes the proposed advantage

Rabbit Hole is the link between those stages. Alice says it built the proprietary dataset over nearly a decade by tracking fraud, extremism, coordinated manipulation, and other adversarial activity across the open web. Its premise is that earlier attack patterns can help identify hostile behavior against AI systems.

Alice says it has more than 150 researchers studying how AI systems can be manipulated or fail. It also says it works with eight of the 10 leading AI model labs, protects more than 3 billion people online, is approaching $100 million in annual recurring revenue, and has grown its AI business by more than 500% over two years.

Those reach and growth figures are company-supplied. The execution test is whether Alice’s historical attack intelligence produces controls that work across both settings: broad model defenses for labs and locally tailored safeguards for enterprise deployments.

Sources

  1. newswire.comAlice Raises $140M to Make Sure AI Does Exactly What It's Supposed to Do
  2. securityweek.comAlice Raises $140M to Expand AI Model Defenses and Enterprise Guardrails

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