Foundation Models, Fortified for Endurance
Embed resilience into foundation models, powered by deep AI security and safety expertise, to withstand evolving threats, real-world misuse, and systemic risk at scale.
Start the ConversationAlice Data Advantage
Alice is the world’s largest collector and manager of adversarial intelligence data. Our data is the cornerstone for protecting platform, tech, and users online.
Learn More >Foundational safety is derived from preventing systemic vulnerabilities.
At Alice, we lead the frontier of AI security and safety, continuously researching how the most powerful models behave, adapt, and fail at scale.
Harmful, Toxic,
or Biased Outputs
Learned patterns systematically producing unsafe or misaligned behavior in downstream usage.
Model and Infrastructure Exploitation
Vulnerabilities resulting in safeguard bypass, data exposure, or behavioral manipulation.
Poisoned Training Data and Backdoors
Compromised training data embedding deep, persistent vulnerabilities and hidden behaviors
Agentic & Ecosystem Level Attacks
Model weaknesses undermining safeguards across agents, tools, and connected AI systems.
Alice helps your models and agents stand tall through every test and trial.
Training Datasets
Build safer, more reliable models through stronger data.
Alice produces safety, security, multimodal, agentic, and skills-based datasets for model, application, and agent training. Human-created, synthetically generated, or collected from online environments, our datasets are suitable for SFT, RLHF, and more. They expose novel risks, alignment failures, and unsafe usage patterns before they propagate downstream.
Evaluations & Red Team
Surface vulnerabilities before they reach production.
Alice combines expert-led and automated red-teaming to stress-test models across text, image, audio, and video under real adversarial conditions. Our evaluation and benchmark datasets are based on Alice's harms taxonomy or customized to your policies, covering both benign and adversarial prompts and scenarios to support confident iteration and release.
Detection Signals
Train guardrails and classifiers on data that reflects the real threat landscape.
Alice provides AIGC and harmful content learning sets purpose-built for guardrail and content classifier creation. Our signals and datasets cover benign, violative, deepfake, and AI-generated slop content based on real GenAI tools and workflows, across abuse types and modalities, so your detectors are grounded in how threats actually behave.
Agentic RL Environments
Test agent behavior across the full range of conditions your models will face.
Alice provides simulated, high-fidelity environments and scenarios for training and testing AI agents and agentic models. Realistic and isolated, our environments support benign and adversarial scenarios across browser-based entities and mock enterprise systems, giving you the coverage needed to validate agent safety before deployment.
Step beyond the looking-glass.
Alice's solutions are powered by Rabbit Hole - our adversarial threat intelligence engine built on billions of real-world data samples collected across nearly a decade of protecting the world's biggest tech platforms.
So AI security and safety is shaped by reality, not assumption.
Deep Harm Area Domain Expertise
Over eight years partnering with top-10 tech platforms on trust and safety across extreme harms spanning safety (CBRNE, deception, political bias, child safety), security and privacy (prompt injections, PII, data exfiltration, malware), and other risks including financial, legal, and medical.
Multilingual & Fully Multimodal
A native speaker network across dozens of languages with support for over 100, including internationalization and localization across media types spanning all input and output combinations: text, image, audio, speech, and video, with full agentic infrastructure and capabilities.
Rapid Execution
Turnaround in days or weeks through automation and global network mobilization.
Lead with Safety. Innovate with Confidence.
GenAI risk addressed early becomes a competitive advantage - enabling responsible releases, sustained trust, and faster innovation.
Ready to take the next step?
What’s New from Alice
Curiouser Soundbites: What a Former Google Cloud CISO Wants Leaders to Know About AI
Everyone's watching the flood of new AI vulnerabilities. Former Google Cloud CISO Phil Venables is watching something else, and it's the shift leaders can't afford to miss.
AI in Healthcare: Protecting Patient Data Without Falling Behind
Your doctor knows things about you that almost nobody else does. So what happens when AI gets access to all of it? Sandy Dunn has spent much of her career worrying about exactly that. She's a healthcare CISO, and her answer is calmer than you'd think: the things that can go wrong aren't new, it's how fast they happen and how far the damage spreads. In this episode, she and Mo get into why HIPAA has become paperwork that protects almost nobody, why the safest data is the data you never collected, and what happens to trust when AI is in the exam room.
It Takes AI to Break AI: The Case for AI Red Teaming
As AI systems gain autonomy, organizations need security approaches built specifically for AI behavior. Learn why AI-driven red teaming is becoming a critical defense layer.
Demystifying AI Red Teaming
Your AI passed every check. That doesn't mean it's safe. Learn how to red team AI systems before adversaries find the gaps you missed.