Unity AI Gateway
Unity AI Gateway provides centralized governance, observability, and spend controls across enterprise AI systems, helping organizations manage agents, tools, models, MCPs, and AI frameworks from a single governed layer. It applies consistent governance across Databricks-hosted AI, external models, coding agents, agent harnesses, and other AI services without locking teams into a single provider or stack. Identity-aware policies control what agents can access, which actions they can take, and which tools they can use, while built-in, custom, and third-party guardrails enforce safety and compliance across prompts, responses, and interactions. It captures prompts, traces, tool calls, payload logs, audit logs, token usage, and policy decisions to monitor behavior, investigate incidents, and support compliance. Centralized cost controls track consumption across users, teams, applications, agents, and providers, with budgets, rate limits, and hard spend caps.
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Llama Guard
Llama Guard is an open-source safeguard model developed by Meta AI to enhance the safety of large language models in human-AI conversations. It functions as an input-output filter, classifying both prompts and responses into safety risk categories, including toxicity, hate speech, and hallucinations. Trained on a curated dataset, Llama Guard achieves performance on par with or exceeding existing moderation tools like OpenAI's Moderation API and ToxicChat. Its instruction-tuned architecture allows for customization, enabling developers to adapt its taxonomy and output formats to specific use cases. Llama Guard is part of Meta's broader "Purple Llama" initiative, which combines offensive and defensive security strategies to responsibly deploy generative AI models. The model weights are publicly available, encouraging further research and adaptation to meet evolving AI safety needs.
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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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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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