Enkrypt AI
Enkrypt AI is an agentic AI security and compliance platform designed to protect AI applications, models, agents, and their interactions throughout deployment. The platform combines continuous red teaming, real-time guardrails, monitoring, and policy enforcement to help organizations identify and mitigate AI security, safety, compliance, and brand risks. Enkrypt AI dynamically tests AI systems with use-case-specific attacks to uncover issues such as prompt injection, jailbreaking, data leakage, hallucinations, bias, harmful content, model drift, and unsafe agent actions. Real-time guardrails analyze AI interactions and block threats as they occur while adapting to changing prompts and emerging risks. Its compliance capabilities translate internal policies and external regulations into automated controls while producing evidence that organizations can use for audits and 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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ZeroDrift
ZeroDrift is an enforcement runtime for AI that checks every AI-generated message against the regulations and company policies that apply before the message is sent. Its Anchor compliance enforcement model combines a purpose-built small language model with a deterministic rules engine to evaluate outputs and return one of four decisions: pass, rewrite, block, or escalate. Every verdict cites the exact rule behind the decision, and rewritten content is checked again before delivery. Organizations can define their own internal policies, restricted lists, approval flows, and communication standards, which ZeroDrift enforces alongside built-in regulatory requirements across AI agents, chat, email, documents, marketing, APIs, and other AI surfaces. Guard provides an enforcement API that can sit in front of any AI agent or LLM, allowing applications to act directly on each verdict without rebuilding the existing AI stack.
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HOL Guard
HOL Guard is a local-first runtime security layer for AI agents that watches what an AI assistant is about to do and stops risky actions before they happen. It sits between the agent and the computer, evaluating supported tool calls and local artifacts for threats such as secret and credential exposure, destructive commands, prompt-injection-driven actions, malicious or changed packages, risky MCP configuration, and unsafe plugins, skills, hooks, and settings. Known threats can be blocked automatically, while ambiguous actions are paused for user approval so people remain in control. Guard runs entirely on the developer’s machine, works offline, and does not upload files, prompts, or passwords. Local checks typically complete in under 50 milliseconds and require no changes to existing code or routines. It supports coding agents including Claude Code, Cursor, Codex, Gemini CLI, OpenCode, Hermes, and OpenClaw, with tailored integrations that inspect actions before execution.
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