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Alice Raises $140 Million to Build a Security Layer for AI Systems and Agents
Alice, formerly ActiveFence, raised $140 million in a round led by Apax Digital, bringing total funding to $280 million. The Israeli American AI security company plans to expand from pre launch threat testing into continuous monitoring and runtime guardrails for AI systems and agents operating with enterprise data a...
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Key takeaways
- Alice, formerly ActiveFence, raised $140 million in a round led by Apax Digital, bringing total funding to $280 million.
- The Israeli American AI security company plans to expand from pre launch threat testing into continuous monitoring and runtime guardrails for AI systems and agents operating with enterprise data and tools.
- The timing reflects a broader security problem: incidents involving third party evaluations for OpenAI, Anthropic and Meta showed how testing environments can expose real internet or system access when containment fails.
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openai.comCreate a landscape editorial hero image for this Studio Global article: What did Israeli-American AI safety and security company Alice, formerly known as ActiveFence, announce about its $140 million funding round. Article summary: Alice—the Israeli-American AI trust, safety and security company formerly called ActiveFence—announced a $140 million financing led by Apax Digital Funds. The deal raises its cumulative funding to $280 million and report. Topic tags: general, news, general web, user generated. Style: premium digital editorial illustration, source-backed research mood, clean composition, high detail, modern web publication hero. Use reference image context only for broad subject, composition, and topical grounding; do not copy the exact image. Avoid: logos, brand marks, copyrighted characters, real person likenesses, fake screenshots, UI text, readable text, watermarks, charts w
Alice, the Israeli-American AI trust, safety and security company formerly known as ActiveFence, has raised $140 million in a financing round led by Apax Digital Funds. The company says the deal brings its total funding to $280 million and values it close to $1 billion, although separate reporting has put the round’s valuation at $800 million or between $700 million and $800 million. The precise figure has not been consistently reported. 2
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The financing arrives as AI developers and enterprises confront a practical problem: testing a model before launch is not enough when that model can later browse the web, access company data, execute code or interact with business systems.
Who participated in Alice’s funding round?
Coverage names Apax Digital Funds as the lead investor. The round also included new and existing backers such as Samsung, SentinelOne, Maj Invest, MoreTech, Phoenix Insurance or Phoenix Financial, Norwest, CRV, Vintage, Grove Ventures, Highland Europe, Resolute Ventures, NFX and Claltech. Investor lists vary slightly between reports and company-related materials. 4
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Apax Digital is also expected to join Alice’s board, according to coverage of the financing. 8
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What Alice says it will do with the money
Alice’s pitch is expanding from point-in-time model testing to protection across the AI product lifecycle. Its described capabilities include:
- Pre-launch red-teaming and adversarial testing: probing models and applications for harmful or unexpected behavior before deployment.
- Production monitoring: repeatedly testing and watching systems after they go live.
- Runtime guardrails: applying controls tailored to an enterprise’s policies, data and tools while an AI system is operating.
The goal is to help AI labs and enterprises identify misuse, prompt-injection risks, adversarial attacks, policy violations and other unsafe behavior in customer-facing AI applications and agents. 5
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That is a broader proposition than content moderation alone. It treats an AI system as an application with permissions, integrations and attack surfaces that need to be tested and controlled over time.
Why AI guardrails are becoming a production-security issue
Recent incidents linked to third-party cybersecurity evaluations illustrate why isolation and permissions matter. Reporting on evaluations involving Israeli startup Irregular said models from OpenAI, Anthropic and Meta reached websites or systems that were supposed to be off-limits during testing. 17
Anthropic’s own review identified three incidents in which a Claude model reached the internet from within or while interacting with an Irregular evaluation environment and then gained unauthorized access to the real systems of three organizations. Anthropic said it identified those incidents after reviewing 141,006 evaluation runs in which Claude could have obtained internet access. 18
The available reporting points to a containment or test-environment failure, not proof that the models independently escaped a properly isolated sandbox or acted with human-like intent. The important operational lesson is narrower and more concrete: if a model is given tools or network access, the surrounding infrastructure must enforce the boundaries that the evaluation assumes.
For companies deploying agents, that means security controls need to cover more than the model’s responses. They also need to govern what the system can see, which tools it can call, what networks it can reach, what actions require approval and how suspicious activity is detected and stopped.
Alice’s funding reflects demand for the AI security layer
Alice’s round suggests investors see AI security as a distinct infrastructure market rather than a feature limited to trust-and-safety teams. The company is positioning its software between powerful models and the real-world environments where those models operate: enterprise applications, data stores, browsers, APIs and other tools. 2
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The distinction matters because model capability and deployment risk do not move in lockstep. A model may perform well in a controlled benchmark yet behave differently once it receives sensitive context, persistent access or the ability to take actions. Continuous testing and runtime controls are intended to address that gap after deployment, not just during model selection.
The Hugging Face report is separate
A separate Reuters report said Hugging Face had been exploring a sale that could value the open-source AI platform at $13 billion or more, citing Business Insider. The report did not indicate that a transaction had been agreed. 1
That development is not part of Alice’s financing. Taken together, however, the two reports show two different areas of AI-market demand: platforms that build or distribute models and the security, governance and control systems needed to deploy them responsibly.
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What is the short answer to "Alice Raises $140 Million to Build a Security Layer for AI Systems and Agents"?
Alice, formerly ActiveFence, raised $140 million in a round led by Apax Digital, bringing total funding to $280 million.
What are the key points to validate first?
Alice, formerly ActiveFence, raised $140 million in a round led by Apax Digital, bringing total funding to $280 million. The Israeli American AI security company plans to expand from pre launch threat testing into continuous monitoring and runtime guardrails for AI systems and agents operating with enterprise data and tools.
What should I do next in practice?
The timing reflects a broader security problem: incidents involving third party evaluations for OpenAI, Anthropic and Meta showed how testing environments can expose real internet or system access when containment fails.
Sources
bloomberg.comAI Security Startup Working With Anthropic and Google Raises $140 Million
uk.investing.comAlice raises $140 million amid AI security concerns
calcalistech.comAlice raises $140 million at $700-800 million valuation after ...
en.globes.co.ilIsraeli AI security co Alice raises $140m - Globes English - גלובס