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Alice

AI safety and security platform (formerly ActiveFence) protecting AI model developers and platforms from abuse, misuse, and rogue model behavior.

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70/100Meaningful Innovator

Overview

Alice, rebranded from ActiveFence in January 2026, builds a safety and security layer for AI models and the platforms built on them. The company started in 2018 as a content-moderation and trust-and-safety data provider for social platforms, then pivoted its core technology toward securing AI models directly: red-teaming foundation models, monitoring for jailbreaks and misuse, and feeding real-world attack pattern data (its “Rabbit Hole” dataset) back into model safety training.

The platform is used by AI labs and large consumer platforms to catch abuse patterns before they scale, drawing on years of trust-and-safety data collection across billions of user interactions. Its differentiator is that depth of real-world abuse data, rather than a lab-only red-teaming exercise, which the company argues produces more realistic coverage of how models get misused in production.

Alice raised a $140 million round in August 2026 led by Apax Digital, with participation from SentinelOne and Samsung, valuing the company between $700 million and $800 million and bringing total funding to roughly $280 million. The company says it is approaching $100 million in annual recurring revenue and protects eight of the world’s ten leading AI model-development labs.

Innovation Matrix Assessment

Innovation Velocity 7/10

Rebranded and re-platformed from a trust-and-safety data vendor to an AI model security company in January 2026, shipping a real-world attack-pattern dataset (Rabbit Hole) alongside the pivot.

Operational Value 8/10

Reportedly protects eight of the world's ten leading AI model-development labs and monitors activity across platforms including Google, Meta, TikTok and Amazon, per Bloomberg and CTech coverage of its funding round.

Market Momentum 8/10

Raised $140M in August 2026 led by Apax Digital with SentinelOne and Samsung participating, at a $700-800M valuation, on top of roughly $280M raised to date; company states it is nearing $100M ARR.

Category Disruption 6/10

Repositions an established trust-and-safety data business toward AI model security rather than introducing an entirely new technical approach; the underlying abuse-data asset is genuinely differentiated but the pivot is strategic more than architectural.

Real-World Efficacy 5/10

Scale claims (labs protected, users covered, ARR) are self-reported by the company; no independent red-team benchmark or named-incident evidence was found in press coverage.

Enduring Relevance 8/10

AI model abuse and jailbreak risk is a growing, durable concern as foundation model deployment scales across consumer and enterprise products.

Why CISOs Should Care

Gives security and trust-and-safety teams a way to catch AI model abuse and jailbreak attempts using data drawn from real-world attack patterns rather than synthetic red-teaming alone.

What Makes It Different

Built on a large, longstanding trust-and-safety data asset from its ActiveFence years, rather than starting from a blank-slate AI red-teaming lab.

The Matrix Verdict

70/100 — MEANINGFUL INNOVATOR

A Meaningful Innovator: well-capitalized, credibly backed by strategic investors, and reportedly protecting major AI labs at real scale, though the evidence is still largely vendor-reported and the core repositioning is recent.

Editorial Note: Claims vs. Verified Findings

Funding amount, valuation, and investor names are independently verified via Bloomberg, CTech, and PYMNTS. Customer scale claims (labs protected, users covered, ARR) are company-reported and not independently confirmed.

Sources