Simaril
Silmaril is a self-healing prompt injection defense designed to protect AI systems from increasingly complex, multi-step attacks that traditional guardrails fail to stop. It operates by wrapping inference calls and evaluating whether an execution sequence is leading toward a harmful outcome, rather than simply filtering inputs. It uses a multihead classifier that analyzes user intent, application context, and execution states together, enabling it to detect indirect injection, multi-turn attack chains, context poisoning, and tool abuse before damage occurs. Silmaril continuously strengthens its defenses through autonomous threat hunting agents that probe systems, discover vulnerabilities, and generate synthetic training data from real attack scenarios. These insights are used to retrain the model automatically, deploying updated protections in under an hour and propagating anonymized defenses across all deployments.
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Alice
Alice (formerly ActiveFence) is a security, safety, and trust platform built to protect AI systems and online platforms in the GenAI era. Powered by the world’s largest adversarial intelligence dataset, Alice safeguards over 3 billion users across more than 120 languages. Its Rabbit Hole intelligence engine continuously analyzes billions of toxic and manipulative data samples to detect emerging threats in real time. The WonderSuite platform includes tools like WonderBuild for pre-launch stress testing, WonderFence for runtime guardrails, and WonderCheck for automated red-teaming. By defending against prompt injection, jailbreaks, governance gaps, and harmful AI behavior, Alice enables enterprises and foundation model labs to innovate with confidence.
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LangProtect
LangProtect is an AI-native security and governance platform that protects LLM and Generative AI applications from prompt injection, jailbreaks, sensitive data leakage, and unsafe or non-compliant outputs. Built for production GenAI, it enforces real-time runtime controls at the AI execution layer by inspecting prompts, model responses, and tool/function calls as they happen. This allows teams to block high-risk behavior before it reaches end users, triggers downstream actions, or exposes confidential data.
LangProtect integrates into existing LLM stacks via an API-first approach with minimal latency and supports cloud, hybrid, and on-prem deployments for enterprise security and data residency needs. It also secures modern architectures such as RAG pipelines and agentic workflows with policy-driven enforcement, continuous visibility, and audit-ready governance.
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ZenGuard AI
ZenGuard AI is a security platform designed to protect AI-driven customer experience agents from potential threats, ensuring they operate safely and effectively. Developed by experts from leading tech companies like Google, Meta, and Amazon, ZenGuard provides low-latency security guardrails that mitigate risks associated with large language model-based AI agents. Safeguards AI agents against prompt injection attacks by detecting and neutralizing manipulation attempts, ensuring secure LLM operation. Identifies and manages sensitive information to prevent data leaks and ensure compliance with privacy regulations. Enforces content policies by restricting AI agents from discussing prohibited subjects, maintaining brand integrity and user safety. The platform also provides a user-friendly interface for policy configuration, enabling real-time updates to security settings.
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