ActiveFence
Enterprise AI governance platform to test, protect, and monitor GenAI apps, agents, and models.
Alice is the go-to for enterprises needing full-lifecycle AI safety with proven scale. Its Rabbit Hole data moat and deep integrations (Databricks, AWS, NVIDIA) outperform tooling-only alternatives. However, no self-serve or low-cost tiers exist — budget accordingly.
Verified 17d ago · liveness 93/100 · cite: rightaichoice.com/tools/activefence
- Frontier model labs needing pre-launch red-teaming and compliance
- Enterprise GenAI deployments in finance, insurance, healthcare, and child safety
- Platform companies with millions of users requiring real-time guardrails across languages
- Teams deploying AI agents that need robust jailbreak and prompt injection defense
- Small teams or startups looking for a free or low-cost basic toxicity filter
- Projects that only need a simple content moderation API without adversarial testing
- Organizations that want a self-serve, no-contact sales pricing model
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Skip Alice if you need a self-serve, free, or low-cost AI safety tool with transparent pricing and no sales engagement.
Pricing is custom and requires a sales call, so you can't estimate costs upfront without engaging the sales team.
Alice targets large enterprises and frontier labs; expect six-figure annual contracts. Competitors like Lakera ($200/month entry) or Arthur ($99/month) are far more budget-friendly for smaller teams. Alice's value is in its data moat and full lifecycle coverage, not in cost efficiency for low-volume use.
In short
ActiveFence — Enterprise AI governance platform to test, protect, and monitor GenAI apps, agents, and models. Best for Frontier model labs needing pre-launch red-teaming and compliance, Enterprise GenAI deployments in finance, insurance, healthcare, and child safety, Platform companies with millions of users requiring real-time guardrails across languages. Contact Sales pricing.
What's new in ActiveFence
Checked 17 days agoAcross the latest 5 updates: 5 news mentions.
Evaluation of Instagram Teen Accounts Report
Report evaluating default and opt-in content protections under real-world and adversarial conditions for Instagram Teen Accounts.
Beneath the Surface: The Growing Ecosystem of AI Nudification Report
Alice analyzed 100 AI nudification websites to uncover how synthetic NCII ecosystems scale.
Building AI Applications in Financial Services Guide
Guide covering governance, model risk, and regulatory obligations for building safe AI in financial services.
Alice Financial Benchmark
Benchmark showing which models gave unauthorized financial advice without jailbreak, to help protect deployments.
Exposing the Hidden Risks of AI Toys Report
Research revealing safety gaps in AI-powered toys, where child-like interactions can lead to inappropriate content.
Viability Score
How likely is ActiveFence to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Pre-launch stress-testing with automated red-teaming (WonderBuild)
- Dynamic runtime guardrails for live apps (WonderFence)
- Continuous red-teaming and drift detection (WonderCheck)
- Adversarial intelligence engine (Rabbit Hole) with billions of toxic samples
- Multi-language support across 120+ languages
- Multi-modal detection: text, image, and emerging modalities
- Policy alignment with custom rules and risk tolerance
- Prompt injection and jailbreak detection
- Integration with Databricks Unity AI Gateway for unified guardrails
- Real-time adaptation to emerging threats
- Agentic AI guardrails for autonomous systems
- Child safety protections for AI toys and child-facing products
- Financial services-specific risk benchmarking (Financial Benchmark)
- Evaluation reports for platform safety (e.g., Instagram Teen Accounts)
About ActiveFence
Alice (formerly ActiveFence) provides the WonderSuite AI governance platform to test, protect, and monitor GenAI applications, agents, and foundation models from build to production. Designed for enterprises, frontier model labs, and platform companies, Alice ensures safe, secure, and compliant AI at scale through three integrated products: WonderBuild for pre-launch stress-testing with automated red-teaming, WonderFence for dynamic runtime guardrails, and WonderCheck for continuous red-teaming and drift detection in production. The platform is powered by Rabbit Hole, a proprietary adversarial intelligence dataset built on billions of toxic, manipulative, and abusive data samples across 120+ languages, enabling multi-modal detection (text, image, and emerging modalities), policy alignment, and real-time adaptation to emerging threats. Alice protects over 3 billion users and handles over 1 billion daily AI-human interactions. Recent research includes an AI nudification ecosystem report, the Alice Financial Benchmark for unauthorized financial advice detection, and an evaluation of Instagram Teen Accounts. Key integrations include Databricks Unity AI Gateway for unified guardrails across models, tools, and agents, as well as cloud partnerships with AWS, Azure, and Google Cloud. Alice also provides agentic AI guardrails for autonomous systems and financial services-specific risk benchmarking. Compared to standalone red-teaming tools or simple content moderation APIs, Alice offers a full lifecycle approach with a proprietary adversarial data moat that outpaces alternatives in coverage and accuracy.
Behind the Verdict
Alice is the most comprehensive AI safety platform we've evaluated for enterprises and frontier labs. Its three-product suite — WonderBuild, WonderFence, WonderCheck — covers the full lifecycle from pre-launch red-teaming to production drift detection, which is rare in a market full of point solutions. The Rabbit Hole adversarial intelligence engine is a genuine differentiator: built on a decade of real-world data across 120+ languages, it enables detection that adapts to emerging threats faster than competitors. This is why Alice protects over 3 billion users and handles over 1 billion daily interactions. Where it bites: pricing is enterprise-only and requires contacting sales — no self-serve or low-cost tiers exist. Small teams or startups with limited budgets should look elsewhere. Also, the platform's depth means a steeper learning curve; you'll need dedicated trust and safety personnel to configure policies and interpret results. Compared to standalone red-teaming tools like Lakera or simple moderation APIs like Azure Content Safety, Alice provides a full lifecycle approach with a proprietary data moat. The Databricks Unity AI Gateway integration (announced June 2026) is a strong move for enterprises already on Databricks. In practice, we'd reach for Alice when shipping a new LLM or agent that needs rigorous pre-launch testing and ongoing monitoring, especially in regulated industries like finance, healthcare, or child safety. The Financial Benchmark and child safety reports published in 2026 show real-world applicability. Skip it if you just need a basic toxicity filter or have a sub-$50K annual budget.
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Real-world workflow fit
Concrete scenarios for the personas ActiveFence actually fits — and what changes day-one when you adopt it.
You need to red-team a new LLM before release to identify vulnerabilities.
Outcome: Use WonderBuild to run automated red-teaming tests across 120+ languages, generating a report of vulnerabilities within hours.
You need to deploy guardrails for a customer-facing financial advice chatbot.
Outcome: Integrate WonderFence via API to block unauthorized financial advice in real-time, using the Financial Benchmark to tune policies.
You need to monitor an AI agent for drift and emerging risks in production.
Outcome: Set up WonderCheck to continuously evaluate agent behavior and receive alerts on new attack vectors.
Use Cases
- Stress-test new GenAI models for safety vulnerabilities before launch.
- Deploy runtime guardrails to block prompt injections and jailbreaks in live chatbots.
- Continuously monitor production AI agents for drift and emerging risks.
- Align AI behavior with regulatory requirements in financial services or healthcare.
- Protect child-facing AI toys from generating inappropriate content.
- Red-team enterprise AI systems using real-world adversarial intelligence.
- Run ongoing automated red-teaming and drift detection for production AI.
Models Under the Hood
as of 2026-07-14
Limitations
- Pricing is not publicly disclosed and requires contacting sales.
- The platform is enterprise-focused, so deployment may require integration effort and dedicated support.
- No self-service tiers or free usage options are mentioned.
as of 2026-06-30
Where the pricing makes sense
The company stage and team size where ActiveFence's pricing actually pencils out — and where peers do it cheaper.
Alice targets large enterprises and frontier labs; expect six-figure annual contracts. Competitors like Lakera ($200/month entry) or Arthur ($99/month) are far more budget-friendly for smaller teams. Alice's value is in its data moat and full lifecycle coverage, not in cost efficiency for low-volume use.
Setup time & first value
How long it actually takes to get something useful out of ActiveFence — broken out by persona, not the marketing-page minute.
For a safety engineer with API access: basic integration in 1–2 days; full lifecycle policies in 1–2 weeks. Enterprise onboarding with dedicated support: 2–4 weeks for comprehensive guardrails across all modalities.
Switching to or from ActiveFence
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From custom in-house safety tooling: Replace with Alice's pre-built classifiers and red-teaming automation, reducing maintenance overhead.
- →From Lakera or Arthur: Migrate by connecting Alice's API endpoints; policy rules can be translated via Alice's policy alignment dashboard.
- ↗To Lakera: Export red-teaming reports and policy rules; Lakera supports similar guardrails but with less adversarial depth.
- ↗To Arthur: Move runtime monitoring to Arthur's platform; expectations adjust for less comprehensive data moat.
Integrations
Resources & Guides
- Resourceactivefence.com
Resources | AI Security, Safety & Trust Ecosystem | Alice
Helpful link from activefence.com
- Documentationactivefence.com
Resources | AI Security, Safety & Trust Ecosystem | Alice
Full product docs from activefence.com
- Guideactivefence.com
Resources | AI Security, Safety & Trust Ecosystem | Alice
In-depth how-to from activefence.com
- Resourceactivefence.com
Resources | AI Security, Safety & Trust Ecosystem | Alice
Helpful link from activefence.com
- Learnactivefence.com
Resources | AI Security, Safety & Trust Ecosystem | Alice
Educational content from activefence.com
Official links
Tools that pair well with ActiveFence
Common stack mates teams adopt alongside ActiveFence, with the specific reason each pairing earns its keep.
Alternatives to ActiveFence
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